Initial commit of dev-config skills and agent configs

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# Engineering
Skills I use daily for code work.
## User-invoked
Reachable only when you type them (`disable-model-invocation: true`).
- **[ask-matt](./ask-matt/SKILL.md)** — Ask which skill or flow fits your situation. A router over the user-invoked skills in this repo.
- **[grill-with-docs](./grill-with-docs/SKILL.md)** — Grilling session that also builds your project's domain model, sharpening terminology and updating `CONTEXT.md` and ADRs inline.
- **[triage](./triage/SKILL.md)** — Move issues through a state machine of triage roles.
- **[improve-codebase-architecture](./improve-codebase-architecture/SKILL.md)** — Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
- **[setup-matt-pocock-skills](./setup-matt-pocock-skills/SKILL.md)** — Configure this repo for the engineering skills (issue tracker, triage labels, domain doc layout). Run once per repo.
- **[to-issues](./to-issues/SKILL.md)** — Break any plan, spec, or PRD into independently-grabbable issues using vertical slices.
- **[to-prd](./to-prd/SKILL.md)** — Turn the current conversation into a PRD and publish it to the issue tracker.
- **[prototype](./prototype/SKILL.md)** — Build a throwaway prototype — a runnable terminal app for state/logic questions, or several toggleable UI variations.
## Model-invoked
Model- or user-reachable (rich trigger phrasing so the model can reach for them).
- **[diagnosing-bugs](./diagnosing-bugs/SKILL.md)** — Disciplined diagnosis loop for hard bugs and performance regressions: reproduce → minimise → hypothesise → instrument → fix → regression-test.
- **[tdd](./tdd/SKILL.md)** — Test-driven development with a red-green-refactor loop. Builds features or fixes bugs one vertical slice at a time.
- **[domain-modeling](./domain-modeling/SKILL.md)** — Actively build and sharpen a project's domain model — challenge terms, stress-test with scenarios, update `CONTEXT.md` and ADRs inline.
- **[codebase-design](./codebase-design/SKILL.md)** — Shared discipline and vocabulary for designing deep modules: small interfaces, clean seams, testable through the interface.
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---
name: diagnosing-bugs
description: Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
---
# Diagnosing Bugs
A discipline for hard bugs. Skip phases only when explicitly justified.
When exploring the codebase, read `CONTEXT.md` (if it exists) to get a clear mental model of the relevant modules, and check ADRs in the area you're touching.
## Phase 1 — Build a feedback loop
**This is the skill.** Everything else is mechanical. If you have a **tight** pass/fail signal for the bug — one that goes red on _this_ bug — you will find the cause; bisection, hypothesis-testing, and instrumentation all just consume it. If you don't have one, no amount of staring at code will save you.
Spend disproportionate effort here. **Be aggressive. Be creative. Refuse to give up.**
### Ways to construct one — try them in roughly this order
1. **Failing test** at whatever seam reaches the bug — unit, integration, e2e.
2. **Curl / HTTP script** against a running dev server.
3. **CLI invocation** with a fixture input, diffing stdout against a known-good snapshot.
4. **Headless browser script** (Playwright / Puppeteer) — drives the UI, asserts on DOM/console/network.
5. **Replay a captured trace.** Save a real network request / payload / event log to disk; replay it through the code path in isolation.
6. **Throwaway harness.** Spin up a minimal subset of the system (one service, mocked deps) that exercises the bug code path with a single function call.
7. **Property / fuzz loop.** If the bug is "sometimes wrong output", run 1000 random inputs and look for the failure mode.
8. **Bisection harness.** If the bug appeared between two known states (commit, dataset, version), automate "boot at state X, check, repeat" so you can `git bisect run` it.
9. **Differential loop.** Run the same input through old-version vs new-version (or two configs) and diff outputs.
10. **HITL bash script.** Last resort. If a human must click, drive _them_ with `scripts/hitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.
Build the right feedback loop, and the bug is 90% fixed.
### Tighten the loop
Treat the loop as a product. Once you have _a_ loop, **tighten** it:
- Can I make it faster? (Cache setup, skip unrelated init, narrow the test scope.)
- Can I make the signal sharper? (Assert on the specific symptom, not "didn't crash".)
- Can I make it more deterministic? (Pin time, seed RNG, isolate filesystem, freeze network.)
A 30-second flaky loop is barely better than no loop; a 2-second deterministic one is tight — a debugging superpower.
### Non-deterministic bugs
The goal is not a clean repro but a **higher reproduction rate**. Loop the trigger 100×, parallelise, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not — keep raising the rate until it's debuggable.
### When you genuinely cannot build a loop
Stop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a captured artifact (HAR file, log dump, core dump, screen recording with timestamps), or (c) permission to add temporary production instrumentation. Do **not** proceed to hypothesise without a loop.
### Completion criterion — a tight loop that goes red
Phase 1 is done when the loop is **tight** and **red-capable**: you can name **one command** — a script path, a test invocation, a curl — that you have **already run at least once** (paste the invocation and its output), and that is:
- [ ] **Red-capable** — it drives the actual bug code path and asserts the **user's exact symptom**, so it can go red on this bug and green once fixed. Not "runs without erroring" — it must be able to _catch this specific bug_.
- [ ] **Deterministic** — same verdict every run (flaky bugs: a pinned, high reproduction rate, per above).
- [ ] **Fast** — seconds, not minutes.
- [ ] **Agent-runnable** — you can run it unattended; a human in the loop only via `scripts/hitl-loop.template.sh`.
If you catch yourself reading code to build a theory before this command exists, **stop — jumping straight to a hypothesis is the exact failure this skill prevents.** No red-capable command, no Phase 2.
## Phase 2 — Reproduce + minimise
Run the loop. Watch it go red — the bug appears.
Confirm:
- [ ] The loop produces the failure mode the **user** described — not a different failure that happens to be nearby. Wrong bug = wrong fix.
- [ ] The failure is reproducible across multiple runs (or, for non-deterministic bugs, reproducible at a high enough rate to debug against).
- [ ] You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix actually addresses it.
### Minimise
Once it's red, shrink the repro to the **smallest scenario that still goes red**. Cut inputs, callers, config, data, and steps **one at a time**, re-running the loop after each cut — keep only what's load-bearing for the failure.
Why bother: a minimal repro shrinks the hypothesis space in Phase 3 (fewer moving parts left to suspect) and becomes the clean regression test in Phase 5.
Done when **every remaining element is load-bearing** — removing any one of them makes the loop go green.
Do not proceed until you have reproduced **and** minimised.
## Phase 3 — Hypothesise
Generate **35 ranked hypotheses** before testing any of them. Single-hypothesis generation anchors on the first plausible idea.
Each hypothesis must be **falsifiable**: state the prediction it makes.
> Format: "If <X> is the cause, then <changing Y> will make the bug disappear / <changing Z> will make it worse."
If you cannot state the prediction, the hypothesis is a vibe — discard or sharpen it.
**Show the ranked list to the user before testing.** They often have domain knowledge that re-ranks instantly ("we just deployed a change to #3"), or know hypotheses they've already ruled out. Cheap checkpoint, big time saver. Don't block on it — proceed with your ranking if the user is AFK.
## Phase 4 — Instrument
Each probe must map to a specific prediction from Phase 3. **Change one variable at a time.**
Tool preference:
1. **Debugger / REPL inspection** if the env supports it. One breakpoint beats ten logs.
2. **Targeted logs** at the boundaries that distinguish hypotheses.
3. Never "log everything and grep".
**Tag every debug log** with a unique prefix, e.g. `[DEBUG-a4f2]`. Cleanup at the end becomes a single grep. Untagged logs survive; tagged logs die.
**Perf branch.** For performance regressions, logs are usually wrong. Instead: establish a baseline measurement (timing harness, `performance.now()`, profiler, query plan), then bisect. Measure first, fix second.
## Phase 5 — Fix + regression test
Write the regression test **before the fix** — but only if there is a **correct seam** for it.
A correct seam is one where the test exercises the **real bug pattern** as it occurs at the call site. If the only available seam is too shallow (single-caller test when the bug needs multiple callers, unit test that can't replicate the chain that triggered the bug), a regression test there gives false confidence.
**If no correct seam exists, that itself is the finding.** Note it. The codebase architecture is preventing the bug from being locked down. Flag this for the next phase.
If a correct seam exists:
1. Turn the minimised repro into a failing test at that seam.
2. Watch it fail.
3. Apply the fix.
4. Watch it pass.
5. Re-run the Phase 1 feedback loop against the original (un-minimised) scenario.
## Phase 6 — Cleanup + post-mortem
Required before declaring done:
- [ ] Original repro no longer reproduces (re-run the Phase 1 loop)
- [ ] Regression test passes (or absence of seam is documented)
- [ ] All `[DEBUG-...]` instrumentation removed (`grep` the prefix)
- [ ] Throwaway prototypes deleted (or moved to a clearly-marked debug location)
- [ ] The hypothesis that turned out correct is stated in the commit / PR message — so the next debugger learns
**Then ask: what would have prevented this bug?** If the answer involves architectural change (no good test seam, tangled callers, hidden coupling) hand off to the `/improve-codebase-architecture` skill with the specifics. Make the recommendation **after** the fix is in, not before — you have more information now than when you started.
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#!/usr/bin/env bash
# Human-in-the-loop reproduction loop.
# Copy this file, edit the steps below, and run it.
# The agent runs the script; the user follows prompts in their terminal.
#
# Usage:
# bash hitl-loop.template.sh
#
# Two helpers:
# step "<instruction>" → show instruction, wait for Enter
# capture VAR "<question>" → show question, read response into VAR
#
# At the end, captured values are printed as KEY=VALUE for the agent to parse.
set -euo pipefail
step() {
printf '\n>>> %s\n' "$1"
read -r -p " [Enter when done] " _
}
capture() {
local var="$1" question="$2" answer
printf '\n>>> %s\n' "$question"
read -r -p " > " answer
printf -v "$var" '%s' "$answer"
}
# --- edit below ---------------------------------------------------------
step "Open the app at http://localhost:3000 and sign in."
capture ERRORED "Click the 'Export' button. Did it throw an error? (y/n)"
capture ERROR_MSG "Paste the error message (or 'none'):"
# --- edit above ---------------------------------------------------------
printf '\n--- Captured ---\n'
printf 'ERRORED=%s\n' "$ERRORED"
printf 'ERROR_MSG=%s\n' "$ERROR_MSG"
@@ -0,0 +1,190 @@
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---
name: frontend-design
description: "Frontend UI: pages, apps, components, polished non-generic design."
license: Complete terms in LICENSE.txt
---
This skill guides creation of distinctive, production-grade frontend interfaces that avoid generic "AI slop" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.
The user provides frontend requirements: a component, page, application, or interface to build. They may include context about the purpose, audience, or technical constraints.
## Design Thinking
Before coding, understand the context and commit to a BOLD aesthetic direction:
- **Purpose**: What problem does this interface solve? Who uses it?
- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction.
- **Constraints**: Technical requirements (framework, performance, accessibility).
- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember?
**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work - the key is intentionality, not intensity.
Then implement working code (HTML/CSS/JS, React, Vue, etc.) that is:
- Production-grade and functional
- Visually striking and memorable
- Cohesive with a clear aesthetic point-of-view
- Meticulously refined in every detail
## Frontend Aesthetics Guidelines
Focus on:
- **Typography**: Choose fonts that are beautiful, unique, and interesting. Avoid generic fonts like Arial and Inter; opt instead for distinctive choices that elevate the frontend's aesthetics; unexpected, characterful font choices. Pair a distinctive display font with a refined body font.
- **Color & Theme**: Commit to a cohesive aesthetic. Use CSS variables for consistency. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.
- **Motion**: Use animations for effects and micro-interactions. Prioritize CSS-only solutions for HTML. Use Motion library for React when available. Focus on high-impact moments: one well-orchestrated page load with staggered reveals (animation-delay) creates more delight than scattered micro-interactions. Use scroll-triggering and hover states that surprise.
- **Spatial Composition**: Unexpected layouts. Asymmetry. Overlap. Diagonal flow. Grid-breaking elements. Generous negative space OR controlled density.
- **Backgrounds & Visual Details**: Create atmosphere and depth rather than defaulting to solid colors. Add contextual effects and textures that match the overall aesthetic. Apply creative forms like gradient meshes, noise textures, geometric patterns, layered transparencies, dramatic shadows, decorative borders, custom cursors, and grain overlays.
NEVER use generic AI-generated aesthetics like overused font families (Inter, Roboto, Arial, system fonts), cliched color schemes (particularly purple gradients on white backgrounds), predictable layouts and component patterns, and cookie-cutter design that lacks context-specific character.
Interpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices (Space Grotesk, for example) across generations.
**IMPORTANT**: Match implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details. Elegance comes from executing the vision well.
Remember: Claude is capable of extraordinary creative work. Don't hold back, show what can truly be created when thinking outside the box and committing fully to a distinctive vision.
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---
name: grill-with-docs
description: A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
disable-model-invocation: true
---
Run a `/grilling` session, using the `/domain-modeling` skill.
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# HTML Report Format
The architectural review is rendered as a single self-contained HTML file in the OS temp directory. Tailwind and Mermaid both come from CDNs. Mermaid handles graph-shaped diagrams reliably; hand-built divs and inline SVG handle the more editorial visuals (mass diagrams, cross-sections). Mix the two — don't lean on Mermaid for everything, it'll start to look generic.
## Scaffold
```html
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<title>Architecture review — {{repo name}}</title>
<script src="https://cdn.tailwindcss.com"></script>
<script type="module">
import mermaid from "https://cdn.jsdelivr.net/npm/mermaid@11/dist/mermaid.esm.min.mjs";
mermaid.initialize({ startOnLoad: true, theme: "neutral", securityLevel: "loose" });
</script>
<style>
/* small custom layer for things Tailwind doesn't cover cleanly:
dashed seam lines, hand-drawn-feeling arrow heads, etc. */
.seam { stroke-dasharray: 4 4; }
.leak { stroke: #dc2626; }
.deep { background: linear-gradient(135deg, #0f172a, #1e293b); }
</style>
</head>
<body class="bg-stone-50 text-slate-900 font-sans">
<main class="max-w-5xl mx-auto px-6 py-12 space-y-12">
<header>...</header>
<section id="candidates" class="space-y-10">...</section>
<section id="top-recommendation">...</section>
</main>
</body>
</html>
```
## Header
Repo name, date, and a compact legend: solid box = module, dashed line = seam, red arrow = leakage, thick dark box = deep module. No introduction paragraph — straight into the candidates.
## Candidate card
The diagrams carry the weight. Prose is sparse, plain, and uses the glossary terms (from the `/codebase-design` skill) without ceremony.
Each candidate is one `<article>`:
- **Title** — short, names the deepening (e.g. "Collapse the Order intake pipeline").
- **Badge row** — recommendation strength (`Strong` = emerald, `Worth exploring` = amber, `Speculative` = slate), plus a tag for the dependency category (`in-process`, `local-substitutable`, `ports & adapters`, `mock`).
- **Files** — monospaced list, `font-mono text-sm`.
- **Before / After diagram** — the centrepiece. Two columns, side by side. See patterns below.
- **Problem** — one sentence. What hurts.
- **Solution** — one sentence. What changes.
- **Wins** — bullets, ≤6 words each. e.g. "Tests hit one interface", "Pricing logic stops leaking", "Delete 4 shallow wrappers".
- **ADR callout** (if applicable) — one line in an amber-tinted box.
No paragraphs of explanation. If the diagram needs a paragraph to be understood, redraw the diagram.
## Diagram patterns
Pick the pattern that fits the candidate. Mix them. Don't make every diagram look the same — variety is part of the point.
### Mermaid graph (the workhorse for dependencies / call flow)
Use a Mermaid `flowchart` or `graph` when the point is "X calls Y calls Z, and look at the mess." Wrap it in a Tailwind-styled card so it doesn't feel parachuted in. Style with classDef to colour leakage edges red and the deep module dark. Sequence diagrams work well for "before: 6 round-trips; after: 1."
```html
<div class="rounded-lg border border-slate-200 bg-white p-4">
<pre class="mermaid">
flowchart LR
A[OrderHandler] --> B[OrderValidator]
B --> C[OrderRepo]
C -.leak.-> D[PricingClient]
classDef leak stroke:#dc2626,stroke-width:2px;
class C,D leak
</pre>
</div>
```
### Hand-built boxes-and-arrows (when Mermaid's layout fights you)
Modules as `<div>`s with borders and labels. Arrows as inline SVG `<line>` or `<path>` elements positioned absolutely over a relative container. Reach for this when you want the "after" diagram to feel like one thick-bordered deep module with greyed-out internals — Mermaid won't render that with the right weight.
### Cross-section (good for layered shallowness)
Stack horizontal bands (`h-12 border-l-4`) to show layers a call passes through. Before: 6 thin layers each doing nothing. After: 1 thick band labelled with the consolidated responsibility.
### Mass diagram (good for "interface as wide as implementation")
Two rectangles per module — one for interface surface area, one for implementation. Before: interface rectangle is nearly as tall as the implementation rectangle (shallow). After: interface rectangle is short, implementation rectangle is tall (deep).
### Call-graph collapse
Before: a tree of function calls rendered as nested boxes. After: the same tree collapsed into one box, with the now-internal calls shown faded inside it.
## Style guidance
- Lean editorial, not corporate-dashboard. Generous whitespace. Serif optional for headings (`font-serif` works well with stone/slate).
- Colour sparingly: one accent (emerald or indigo) plus red for leakage and amber for warnings.
- Keep diagrams ~320px tall so before/after sits comfortably side by side without scrolling.
- Use `text-xs uppercase tracking-wider` for module labels inside diagrams — they should read as schematic, not as UI.
- The only scripts are the Tailwind CDN and the Mermaid ESM import. The report is otherwise static — no app code, no interactivity beyond Mermaid's own rendering.
## Top recommendation section
One larger card. Candidate name, one sentence on why, anchor link to its card. That's it.
## Tone
Plain English, concise — but the architectural nouns and verbs come straight from the `/codebase-design` skill. Concision is not an excuse to drift.
**Use exactly:** module, interface, implementation, depth, deep, shallow, seam, adapter, leverage, locality.
**Never substitute:** component, service, unit (for module) · API, signature (for interface) · boundary (for seam) · layer, wrapper (for module, when you mean module).
**Phrasings that fit the style:**
- "Order intake module is shallow — interface nearly matches the implementation."
- "Pricing leaks across the seam."
- "Deepen: one interface, one place to test."
- "Two adapters justify the seam: HTTP in prod, in-memory in tests."
**Wins bullets** name the gain in glossary terms: *"locality: bugs concentrate in one module"*, *"leverage: one interface, N call sites"*, *"interface shrinks; implementation absorbs the wrappers"*. Don't write *"easier to maintain"* or *"cleaner code"* — those terms aren't in the glossary and don't earn their place.
No hedging, no throat-clearing, no "it's worth noting that…". If a sentence could be a bullet, make it a bullet. If a bullet could be cut, cut it. If a term isn't in the `/codebase-design` glossary, reach for one that is before inventing a new one.
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---
name: improve-codebase-architecture
description: Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
disable-model-invocation: true
---
# Improve Codebase Architecture
Surface architectural friction and propose **deepening opportunities** — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.
This command is _informed_ by the project's domain model and built on a shared design vocabulary:
- Run the `/codebase-design` skill for the architecture vocabulary (**module**, **interface**, **depth**, **seam**, **adapter**, **leverage**, **locality**) and its principles (the deletion test, "the interface is the test surface", "one adapter = hypothetical seam, two = real"). Use these terms exactly in every suggestion — don't drift into "component," "service," "API," or "boundary."
- The domain language in `CONTEXT.md` gives names to good seams; ADRs in `docs/adr/` record decisions this command should not re-litigate.
## Process
### 1. Explore
Read the project's domain glossary (`CONTEXT.md`) and any ADRs in the area you're touching first.
Then use the Agent tool with `subagent_type=Explore` to walk the codebase. Don't follow rigid heuristics — explore organically and note where you experience friction:
- Where does understanding one concept require bouncing between many small modules?
- Where are modules **shallow** — interface nearly as complex as the implementation?
- Where have pure functions been extracted just for testability, but the real bugs hide in how they're called (no **locality**)?
- Where do tightly-coupled modules leak across their seams?
- Which parts of the codebase are untested, or hard to test through their current interface?
Apply the **deletion test** to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? A "yes, concentrates" is the signal you want.
### 2. Present candidates as an HTML report
Write a self-contained HTML file to the OS temp directory so nothing lands in the repo. Resolve the temp dir from `$TMPDIR`, falling back to `/tmp` (or `%TEMP%` on Windows), and write to `<tmpdir>/architecture-review-<timestamp>.html` so each run gets a fresh file. Open it for the user — `xdg-open <path>` on Linux, `open <path>` on macOS, `start <path>` on Windows — and tell them the absolute path.
The report uses **Tailwind via CDN** for layout and styling, and **Mermaid via CDN** for diagrams where a graph/flow/sequence reliably communicates the structure. Mix Mermaid with hand-crafted CSS/SVG visuals — use Mermaid when relationships are graph-shaped (call graphs, dependencies, sequences), and hand-built divs/SVG when you want something more editorial (mass diagrams, cross-sections, collapse animations). Each candidate gets a **before/after visualisation**. Be visual.
For each candidate, render a card with:
- **Files** — which files/modules are involved
- **Problem** — why the current architecture is causing friction
- **Solution** — plain English description of what would change
- **Benefits** — explained in terms of locality and leverage, and how tests would improve
- **Before / After diagram** — side-by-side, custom-drawn, illustrating the shallowness and the deepening
- **Recommendation strength** — one of `Strong`, `Worth exploring`, `Speculative`, rendered as a badge
End the report with a **Top recommendation** section: which candidate you'd tackle first and why.
**Use CONTEXT.md vocabulary for the domain, and the `/codebase-design` vocabulary for the architecture.** If `CONTEXT.md` defines "Order," talk about "the Order intake module" — not "the FooBarHandler," and not "the Order service."
**ADR conflicts**: if a candidate contradicts an existing ADR, only surface it when the friction is real enough to warrant revisiting the ADR. Mark it clearly in the card (e.g. a warning callout: _"contradicts ADR-0007 — but worth reopening because…"_). Don't list every theoretical refactor an ADR forbids.
See [HTML-REPORT.md](HTML-REPORT.md) for the full HTML scaffold, diagram patterns, and styling guidance.
Do NOT propose interfaces yet. After the file is written, ask the user: "Which of these would you like to explore?"
### 3. Grilling loop
Once the user picks a candidate, run the `/grilling` skill to walk the design tree with them — constraints, dependencies, the shape of the deepened module, what sits behind the seam, what tests survive.
Side effects happen inline as decisions crystallize — run the `/domain-modeling` skill to keep the domain model current as you go:
- **Naming a deepened module after a concept not in `CONTEXT.md`?** Add the term to `CONTEXT.md`. Create the file lazily if it doesn't exist.
- **Sharpening a fuzzy term during the conversation?** Update `CONTEXT.md` right there.
- **User rejects the candidate with a load-bearing reason?** Offer an ADR, framed as: _"Want me to record this as an ADR so future architecture reviews don't re-suggest it?"_ Only offer when the reason would actually be needed by a future explorer to avoid re-suggesting the same thing — skip ephemeral reasons ("not worth it right now") and self-evident ones.
- **Want to explore alternative interfaces for the deepened module?** Run the `/codebase-design` skill and use its design-it-twice parallel sub-agent pattern.
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---
name: tdd
description: Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
---
# Test-Driven Development
## Philosophy
**Core principle**: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't.
**Good tests** are integration-style: they exercise real code paths through public APIs. They describe _what_ the system does, not _how_ it does it. A good test reads like a specification - "user can checkout with valid cart" tells you exactly what capability exists. These tests survive refactors because they don't care about internal structure.
**Bad tests** are coupled to implementation. They mock internal collaborators, test private methods, or verify through external means (like querying a database directly instead of using the interface). The warning sign: your test breaks when you refactor, but behavior hasn't changed. If you rename an internal function and tests fail, those tests were testing implementation, not behavior.
See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.
## Anti-Pattern: Horizontal Slices
**DO NOT write all tests first, then all implementation.** This is "horizontal slicing" - treating RED as "write all tests" and GREEN as "write all code."
This produces **crap tests**:
- Tests written in bulk test _imagined_ behavior, not _actual_ behavior
- You end up testing the _shape_ of things (data structures, function signatures) rather than user-facing behavior
- Tests become insensitive to real changes - they pass when behavior breaks, fail when behavior is fine
- You outrun your headlights, committing to test structure before understanding the implementation
**Correct approach**: Vertical slices via tracer bullets. One test → one implementation → repeat. Each test responds to what you learned from the previous cycle. Because you just wrote the code, you know exactly what behavior matters and how to verify it.
```
WRONG (horizontal):
RED: test1, test2, test3, test4, test5
GREEN: impl1, impl2, impl3, impl4, impl5
RIGHT (vertical):
RED→GREEN: test1→impl1
RED→GREEN: test2→impl2
RED→GREEN: test3→impl3
...
```
## Workflow
### 1. Planning
When exploring the codebase, read `CONTEXT.md` (if it exists) so that test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.
Before writing any code:
- [ ] Confirm with user what interface changes are needed
- [ ] Confirm with user which behaviors to test (prioritize)
- [ ] Identify opportunities for deep modules (small interface, deep implementation) — run the `/codebase-design` skill for the vocabulary and the testability checks
- [ ] List the behaviors to test (not implementation steps)
- [ ] Get user approval on the plan
Ask: "What should the public interface look like? Which behaviors are most important to test?"
**You can't test everything.** Confirm with the user exactly which behaviors matter most. Focus testing effort on critical paths and complex logic, not every possible edge case.
### 2. Tracer Bullet
Write ONE test that confirms ONE thing about the system:
```
RED: Write test for first behavior → test fails
GREEN: Write minimal code to pass → test passes
```
This is your tracer bullet - proves the path works end-to-end.
### 3. Incremental Loop
For each remaining behavior:
```
RED: Write next test → fails
GREEN: Minimal code to pass → passes
```
Rules:
- One test at a time
- Only enough code to pass current test
- Don't anticipate future tests
- Keep tests focused on observable behavior
### 4. Refactor
After all tests pass, look for [refactor candidates](refactoring.md):
- [ ] Extract duplication
- [ ] Deepen modules (move complexity behind simple interfaces)
- [ ] Apply SOLID principles where natural
- [ ] Consider what new code reveals about existing code
- [ ] Run tests after each refactor step
**Never refactor while RED.** Get to GREEN first.
## Checklist Per Cycle
```
[ ] Test describes behavior, not implementation
[ ] Test uses public interface only
[ ] Test would survive internal refactor
[ ] Code is minimal for this test
[ ] No speculative features added
```
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# When to Mock
Mock at **system boundaries** only:
- External APIs (payment, email, etc.)
- Databases (sometimes - prefer test DB)
- Time/randomness
- File system (sometimes)
Don't mock:
- Your own classes/modules
- Internal collaborators
- Anything you control
## Designing for Mockability
At system boundaries, design interfaces that are easy to mock:
**1. Use dependency injection**
Pass external dependencies in rather than creating them internally:
```typescript
// Easy to mock
function processPayment(order, paymentClient) {
return paymentClient.charge(order.total);
}
// Hard to mock
function processPayment(order) {
const client = new StripeClient(process.env.STRIPE_KEY);
return client.charge(order.total);
}
```
**2. Prefer SDK-style interfaces over generic fetchers**
Create specific functions for each external operation instead of one generic function with conditional logic:
```typescript
// GOOD: Each function is independently mockable
const api = {
getUser: (id) => fetch(`/users/${id}`),
getOrders: (userId) => fetch(`/users/${userId}/orders`),
createOrder: (data) => fetch('/orders', { method: 'POST', body: data }),
};
// BAD: Mocking requires conditional logic inside the mock
const api = {
fetch: (endpoint, options) => fetch(endpoint, options),
};
```
The SDK approach means:
- Each mock returns one specific shape
- No conditional logic in test setup
- Easier to see which endpoints a test exercises
- Type safety per endpoint
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# Refactor Candidates
After TDD cycle, look for:
- **Duplication** → Extract function/class
- **Long methods** → Break into private helpers (keep tests on public interface)
- **Shallow modules** → Combine or deepen
- **Feature envy** → Move logic to where data lives
- **Primitive obsession** → Introduce value objects
- **Existing code** the new code reveals as problematic
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# Good and Bad Tests
## Good Tests
**Integration-style**: Test through real interfaces, not mocks of internal parts.
```typescript
// GOOD: Tests observable behavior
test("user can checkout with valid cart", async () => {
const cart = createCart();
cart.add(product);
const result = await checkout(cart, paymentMethod);
expect(result.status).toBe("confirmed");
});
```
Characteristics:
- Tests behavior users/callers care about
- Uses public API only
- Survives internal refactors
- Describes WHAT, not HOW
- One logical assertion per test
## Bad Tests
**Implementation-detail tests**: Coupled to internal structure.
```typescript
// BAD: Tests implementation details
test("checkout calls paymentService.process", async () => {
const mockPayment = jest.mock(paymentService);
await checkout(cart, payment);
expect(mockPayment.process).toHaveBeenCalledWith(cart.total);
});
```
Red flags:
- Mocking internal collaborators
- Testing private methods
- Asserting on call counts/order
- Test breaks when refactoring without behavior change
- Test name describes HOW not WHAT
- Verifying through external means instead of interface
```typescript
// BAD: Bypasses interface to verify
test("createUser saves to database", async () => {
await createUser({ name: "Alice" });
const row = await db.query("SELECT * FROM users WHERE name = ?", ["Alice"]);
expect(row).toBeDefined();
});
// GOOD: Verifies through interface
test("createUser makes user retrievable", async () => {
const user = await createUser({ name: "Alice" });
const retrieved = await getUser(user.id);
expect(retrieved.name).toBe("Alice");
});
```
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---
name: to-issues
description: Break a plan, spec, or PRD into independently-grabbable issues on the project issue tracker using tracer-bullet vertical slices.
disable-model-invocation: true
---
# To Issues
Break a plan into independently-grabbable issues using vertical slices (tracer bullets).
The issue tracker and triage label vocabulary should have been provided to you — run `/setup-matt-pocock-skills` if not.
## Process
### 1. Gather context
Work from whatever is already in the conversation context. If the user passes an issue reference (issue number, URL, or path) as an argument, fetch it from the issue tracker and read its full body and comments.
### 2. Explore the codebase (optional)
If you have not already explored the codebase, do so to understand the current state of the code. Issue titles and descriptions should use the project's domain glossary vocabulary, and respect ADRs in the area you're touching.
Look for opportunities to prefactor the code to make the implementation easier. "Make the change easy, then make the easy change."
### 3. Draft vertical slices
Break the plan into **tracer bullet** issues. Each issue is a thin vertical slice that cuts through ALL integration layers end-to-end, NOT a horizontal slice of one layer.
<vertical-slice-rules>
- Each slice delivers a narrow but COMPLETE path through every layer (schema, API, UI, tests)
- A completed slice is demoable or verifiable on its own
- Any prefactoring should be done first
</vertical-slice-rules>
### 4. Quiz the user
Present the proposed breakdown as a numbered list. For each slice, show:
- **Title**: short descriptive name
- **Blocked by**: which other slices (if any) must complete first
- **User stories covered**: which user stories this addresses (if the source material has them)
Ask the user:
- Does the granularity feel right? (too coarse / too fine)
- Are the dependency relationships correct?
- Should any slices be merged or split further?
Iterate until the user approves the breakdown.
### 5. Publish the issues to the issue tracker
For each approved slice, publish a new issue to the issue tracker. Use the issue body template below. These issues are considered ready for AFK agents, so publish them with the correct triage label unless instructed otherwise.
Publish issues in dependency order (blockers first) so you can reference real issue identifiers in the "Blocked by" field.
<issue-template>
## Parent
A reference to the parent issue on the issue tracker (if the source was an existing issue, otherwise omit this section).
## What to build
A concise description of this vertical slice. Describe the end-to-end behavior, not layer-by-layer implementation.
Avoid specific file paths or code snippets — they go stale fast. Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it here and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.
## Acceptance criteria
- [ ] Criterion 1
- [ ] Criterion 2
- [ ] Criterion 3
## Blocked by
- A reference to the blocking ticket (if any)
Or "None - can start immediately" if no blockers.
</issue-template>
Do NOT close or modify any parent issue.
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---
name: to-prd
description: Turn the current conversation into a PRD and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.
disable-model-invocation: true
---
This skill takes the current conversation context and codebase understanding and produces a PRD. Do NOT interview the user — just synthesize what you already know.
The issue tracker and triage label vocabulary should have been provided to you — run `/setup-matt-pocock-skills` if not.
## Process
1. Explore the repo to understand the current state of the codebase, if you haven't already. Use the project's domain glossary vocabulary throughout the PRD, and respect any ADRs in the area you're touching.
2. Sketch out the seams at which you're going to test the feature. Existing seams should be preferred to new ones. Use the highest seam possible. If new seams are needed, propose them at the highest point you can. The fewer seams across the codebase, the better - the ideal number is one.
Check with the user that these seams match their expectations.
3. Write the PRD using the template below, then publish it to the project issue tracker. Apply the `ready-for-agent` triage label - no need for additional triage.
<prd-template>
## Problem Statement
The problem that the user is facing, from the user's perspective.
## Solution
The solution to the problem, from the user's perspective.
## User Stories
A LONG, numbered list of user stories. Each user story should be in the format of:
1. As an <actor>, I want a <feature>, so that <benefit>
<user-story-example>
1. As a mobile bank customer, I want to see balance on my accounts, so that I can make better informed decisions about my spending
</user-story-example>
This list of user stories should be extremely extensive and cover all aspects of the feature.
## Implementation Decisions
A list of implementation decisions that were made. This can include:
- The modules that will be built/modified
- The interfaces of those modules that will be modified
- Technical clarifications from the developer
- Architectural decisions
- Schema changes
- API contracts
- Specific interactions
Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.
Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it within the relevant decision and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.
## Testing Decisions
A list of testing decisions that were made. Include:
- A description of what makes a good test (only test external behavior, not implementation details)
- Which modules will be tested
- Prior art for the tests (i.e. similar types of tests in the codebase)
## Out of Scope
A description of the things that are out of scope for this PRD.
## Further Notes
Any further notes about the feature.
</prd-template>
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# Misc
Tools I keep around but rarely use.
- **[git-guardrails-claude-code](./git-guardrails-claude-code/SKILL.md)** — Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, etc.) before they execute.
- **[migrate-to-shoehorn](./migrate-to-shoehorn/SKILL.md)** — Migrate test files from `as` type assertions to @total-typescript/shoehorn.
- **[scaffold-exercises](./scaffold-exercises/SKILL.md)** — Create exercise directory structures with sections, problems, solutions, and explainers.
- **[setup-pre-commit](./setup-pre-commit/SKILL.md)** — Set up Husky pre-commit hooks with lint-staged, Prettier, type checking, and tests.
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---
name: codex-debugging
description: "Codex debugging: codex-rs core/tui/exec/cli/app-server/config."
---
# Codex Debugging
Use when investigating Codex CLI/app behavior, config parsing, tool behavior, prompts, MCP/app wiring, or runtime bugs.
## Source First
Prefer local source before web/docs:
```bash
cd ~/Projects/codex
sed -n '1,220p' codex-rs/AGENTS.md
```
Then search targeted areas:
```bash
rg "<symbol|setting|error|feature>" codex-rs/{core,tui,exec,cli,app-server,app-server-protocol,config}
```
## Workflow
1. Identify whether the behavior is CLI, TUI, app server, protocol, config, or exec/tooling.
2. Read the owning module and adjacent tests before proposing changes.
3. Check local config in `~/.codex/config.toml` only after understanding the source contract.
4. Prefer small repros or focused tests over broad speculation.
## Notes
- For OpenAI API/product docs, use the official-docs path only when source is insufficient.
- For local browser automation in CLI, use `$browser-use`; the bundled Browser plugin is Codex app-only.
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---
name: git-guardrails-claude-code
description: Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute. Use when user wants to prevent destructive git operations, add git safety hooks, or block git push/reset in Claude Code.
---
# Setup Git Guardrails
Sets up a PreToolUse hook that intercepts and blocks dangerous git commands before Claude executes them.
## What Gets Blocked
- `git push` (all variants including `--force`)
- `git reset --hard`
- `git clean -f` / `git clean -fd`
- `git branch -D`
- `git checkout .` / `git restore .`
When blocked, Claude sees a message telling it that it does not have authority to access these commands.
## Steps
### 1. Ask scope
Ask the user: install for **this project only** (`.claude/settings.json`) or **all projects** (`~/.claude/settings.json`)?
### 2. Copy the hook script
The bundled script is at: [scripts/block-dangerous-git.sh](scripts/block-dangerous-git.sh)
Copy it to the target location based on scope:
- **Project**: `.claude/hooks/block-dangerous-git.sh`
- **Global**: `~/.claude/hooks/block-dangerous-git.sh`
Make it executable with `chmod +x`.
### 3. Add hook to settings
Add to the appropriate settings file:
**Project** (`.claude/settings.json`):
```json
{
"hooks": {
"PreToolUse": [
{
"matcher": "Bash",
"hooks": [
{
"type": "command",
"command": "\"$CLAUDE_PROJECT_DIR\"/.claude/hooks/block-dangerous-git.sh"
}
]
}
]
}
}
```
**Global** (`~/.claude/settings.json`):
```json
{
"hooks": {
"PreToolUse": [
{
"matcher": "Bash",
"hooks": [
{
"type": "command",
"command": "~/.claude/hooks/block-dangerous-git.sh"
}
]
}
]
}
}
```
If the settings file already exists, merge the hook into existing `hooks.PreToolUse` array — don't overwrite other settings.
### 4. Ask about customization
Ask if user wants to add or remove any patterns from the blocked list. Edit the copied script accordingly.
### 5. Verify
Run a quick test:
```bash
echo '{"tool_input":{"command":"git push origin main"}}' | <path-to-script>
```
Should exit with code 2 and print a BLOCKED message to stderr.
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#!/bin/bash
INPUT=$(cat)
COMMAND=$(echo "$INPUT" | jq -r '.tool_input.command')
DANGEROUS_PATTERNS=(
"git push"
"git reset --hard"
"git clean -fd"
"git clean -f"
"git branch -D"
"git checkout \."
"git restore \."
"push --force"
"reset --hard"
)
for pattern in "${DANGEROUS_PATTERNS[@]}"; do
if echo "$COMMAND" | grep -qE "$pattern"; then
echo "BLOCKED: '$COMMAND' matches dangerous pattern '$pattern'. The user has prevented you from doing this." >&2
exit 2
fi
done
exit 0
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---
name: github-deep-review
description: "GitHub deep review: bugs, PRs, best fix, stale-or-real, read code first."
---
# GitHub Deep Review
Review like Peter: high-confidence, evidence-first, code-aware, and willing to say "not proven" when the trail is weak. The goal is not a generic summary. The goal is to understand the bug class, find the real cause if possible, decide the best fix after reading enough code, and call out whether a larger refactor would improve the design.
## Start
Use `gh`, not web browsing, for GitHub refs:
```bash
gh issue view <n> --json number,title,state,author,body,comments,labels,updatedAt,url
gh pr view <n> --json number,title,state,author,body,comments,reviews,files,commits,statusCheckRollup,mergeStateStatus,headRefName,headRepositoryOwner,url
gh pr diff <n> --patch
```
For PRs, collect author context by default unless the author is Peter (`steipete` or an obvious Peter-owned account). Use the local workflow in `~/Projects/agent-scripts/skills/github-author-context/SKILL.md` and include a short `Author context:` block near the top of the review when the author is not Peter.
After merge/rejection/close/review, use that same author-context workflow to append a contributor note only when the interaction creates durable future-review signal.
For repo-local review, also inspect:
```bash
git status --short --branch
git fetch origin
git log --oneline --decorate -20
rg "<key symbol/error/config/endpoint>"
```
If the repo has local instructions, issue/PR skills, docs lists, test guidance, or maintainer runbooks, read those before deciding.
## Review Contract
Always answer these, explicitly:
- URL/ref: issue or PR number and affected surface.
- What is the bug or behavior being fixed?
- Can we identify the root cause? If yes, where in code and why. If no, what evidence is missing.
- For regressions, who/what introduced it and when? Include commit/PR provenance when traceable by bounded history; say unknown instead of guessing.
- Is the current/proposed fix the best possible fix after reading adjacent code?
- Would a bigger refactor improve correctness, clarity, or future maintainability?
- What proof exists: tests, live repro, CI checks, docs, dependency docs/source, shipped/current behavior.
- What remains risky or unverified.
## Code Reading Depth
Read past the first touched file. Follow the real call path:
- entrypoint -> validation/parsing -> routing/dispatch -> owner module -> shared helper -> persistence/network/runtime boundary
- config/schema/docs -> runtime usage -> doctor/migration/fix path
- provider/channel/plugin owner code -> generic core seam, only if multiple owners need it
- tests around the touched surface plus adjacent regression tests
When behavior depends on a dependency, read the upstream docs/source/types or current package contract before assuming.
Prefer current source and executable proof over issue comments. Treat stale comments, old CI, and old release behavior as hints until rechecked.
## Provenance
For bug/regression reviews, include a compact `Provenance:` answer when feasible:
- Use `git log -S/-G`, `git blame`, linked PRs/issues, and tests.
- Separate author, committer/merger, and current PR author when they differ.
- Phrase as `introduced by`, `made visible by`, or `carried forward by`.
- Include confidence: `clear`, `likely`, or `unknown`.
- For features, docs, refactors, or untraceable bugs, write `N/A` or say what evidence is missing.
## Fix Quality Bar
Good fixes usually:
- live at the ownership boundary where the bug belongs
- preserve public/backward-compatible behavior unless the issue is about retiring it
- add a regression test at the smallest meaningful seam
- avoid broad special cases, hidden migrations, semantic sentinels, and provider/channel IDs in generic core
- update docs/changelog when user-visible behavior changes
- fail clearly in runtime paths and repair through doctor/migration paths when that is the established contract
Call out when a fix is only symptom-level. If a slightly larger refactor makes the invariant obvious and reduces future bugs, recommend it. If the refactor widens risk without improving the bug class, say so.
## PR Review Shape
Lead with findings when reviewing a PR. Findings need file/line/symbol references and a concrete failure mode. Avoid vague "consider" comments.
If no blocking issues:
- say no blocking correctness issues found
- list the strongest proof checked
- name residual risk/test gaps
- answer whether the design is the best available shape
Do not approve, comment, close, merge, push, or land unless the user asked for that action.
## Issue Review Shape
For bugs/issues:
1. Reconstruct the reporter's scenario and affected version/surface.
2. Check whether current `main` already fixes it.
3. Reproduce or create a minimal local/live proof when feasible.
4. If clear, identify root cause and proposed fix.
5. If solved on `main`, only comment/close when the user asks; include proof and the canonical commit/PR if known.
If reproduction is not feasible, say exactly what blocks it and what evidence would make the decision reliable.
## Output Template
Use this shape when the user asks "what is this about", "is this the best fix", or "what did we fix":
```text
Ref: #123 / PR #456
Surface: <runtime/CLI/provider/channel/docs>
Bug: <one or two sentences>
Cause: <code path + confidence>
Provenance: <introduced/made visible/carried forward by commit/PR/date, or N/A/unknown>
Best fix: <what should change and why>
Refactor: <yes/no, specific shape>
Proof: <tests/live/CI/source/dependency docs>
Risk: <remaining uncertainty>
```
Keep it concise, but do not skip the cause/fix/refactor/proof decision.
@@ -0,0 +1,4 @@
interface:
display_name: "GitHub Deep Review"
short_description: "Review GitHub issues and PRs with proof"
default_prompt: "Use $github-deep-review to inspect this GitHub issue or PR, read the relevant code paths, identify the root cause, judge the best fix, and call out useful refactors."
+317
View File
@@ -0,0 +1,317 @@
---
name: "github-project-triage"
description: "GitHub issue/PR triage: queues, CI, blockers, risk, proof, next actions."
---
# GitHub Project Triage
Always use this skill when the user types `triage`, unless the request explicitly targets a non-GitHub domain. From inside a repo, use the current GitHub project by default. Triage means maintainer-facing item cards: URL, what each issue/PR is about, why it matters, author trust, fit, risk, proof/test state, blockers, and next action. Never return only queue numbers or opaque refs.
Output is URL-first: every surfaced issue/PR/repo item must include its GitHub URL in the first line or first sentence for that item. If giving a shortlist, print one URL per item.
Use RepoBar as the first pass only for broad queue discovery across relevant owners/orgs. RepoBar is faster and more profile-aware than hand-rolling `gh repo list` loops, and it already understands repo activity, issue counts, PR counts, local projects, auth, cache, and filters.
## Setup
Prefer a real `repobar` binary when installed. In this workspace it may only exist as a SwiftPM product in `~/Projects/RepoBar`.
```bash
repobar_cmd() {
if command -v repobar >/dev/null 2>&1; then
repobar "$@"
elif [ -x "$HOME/Projects/RepoBar/.build/debug/repobarcli" ]; then
"$HOME/Projects/RepoBar/.build/debug/repobarcli" "$@"
else
swift run --package-path "$HOME/Projects/RepoBar" repobarcli "$@"
fi
}
repobar_cmd status --json
```
Default owners for broad triage: `steipete`, `openclaw`. For broad/default queue triage, include a detail pass for `openclaw/openclaw` even if it is not the first repo by count, because it is the main ClawdBot/OpenClaw queue. Do not include `amantus-ai` or other owners unless the user names them, the current repo is already under that owner, or the task explicitly asks for all/everything. For an exact owner-specific task, do not broaden beyond the named owner.
## Local Repo Gate
Before starting work inside any local project, verify the checkout is ready:
```bash
git status --short --branch
git branch --show-current
git pull --ff-only
git status --short --branch
```
Proceed only when the branch is `main`, the pull succeeds, and the worktree is clean. If the branch is not `main`, the pull fails, or `git status --short` shows changes, stop and ask Peter what to do. Do not switch branches, stash, commit, reset, restore, or clean without explicit direction.
## Scope Rule
If the user says `triage` and the current working directory is a Git repo with a GitHub remote, triage only that project. Do not broaden to all Peter/org queues unless the user says `broad`, `all`, `everything`, names multiple owners/orgs, or asks for cross-repo triage.
If the repo has `VISION.md`, read it before judging what can be handled autonomously. Use it as the product-fit source of truth, then apply this skill's risk/testability rules. If no `VISION.md` exists, use the autonomous-fit rules below.
Find the current project:
```bash
repo=$(gh repo view --json nameWithOwner --jq .nameWithOwner 2>/dev/null || true)
if [ -z "$repo" ]; then
url=$(git remote get-url origin 2>/dev/null || true)
repo=$(printf '%s\n' "$url" |
sed -E 's#^git@github.com:##; s#^https://github.com/##; s#\\.git$##')
fi
printf '%s\n' "$repo"
```
Current-project triage starts with:
```bash
gh issue list --repo "$repo" --state open --limit 50 \
--json number,title,author,labels,createdAt,updatedAt,url
gh pr list --repo "$repo" --state open --limit 50 \
--json number,title,author,isDraft,reviewDecision,mergeStateStatus,createdAt,updatedAt,url
```
Before acting on any issue or PR, read all comments and treat Peter/owner comments as authoritative routing instructions. If Peter says it looks good, needs changes, is superseded, is product-approved, or is not wanted, that overrides bot labels and ordinary triage judgment. If there is no Peter/owner comment, use maintainer judgment and say that the call is yours.
Then inspect enough detail to explain every surfaced item. For small queues (about 10 open items or fewer), inspect all items. For larger queues, inspect the top priority slice and say what was not expanded.
```bash
gh issue view <n> --repo "$repo" \
--json number,title,author,body,comments,labels,createdAt,updatedAt,url
gh pr view <n> --repo "$repo" \
--json number,title,author,body,comments,files,commits,isDraft,reviewDecision,mergeStateStatus,statusCheckRollup,createdAt,updatedAt,url
gh pr diff <n> --repo "$repo" --patch
```
Only comment, close, merge, rerun, or patch with strong evidence.
## Triage Output
When the user says `triage`, always scan open issues and open PRs for the current repo. Return:
- `Autonomous candidates`: items that appear fixable/landable without more product input, with URL, why it qualifies, required verification, and confidence. This is a selection for review, not permission to start work unless the user also asks for autonomous execution.
- `Needs Peter`: items blocked on Peter/owner decision, product direction, missing credentials/access, live-provider proof that cannot be obtained, security/privacy judgment, or an authoritative Peter comment requesting changes.
- `Defer/close/supersede`: stale, duplicate, lower-quality, or overlapping items where the likely action is not new code.
For every plausible autonomous candidate, use available high-reasoning subagents, oracle, or independent agent review to check feasibility before presenting it when tool support exists. Give the subagent only task-local evidence and ask whether the item can be completed autonomously, what verification is required, and what could make it unsafe. If subagents are unavailable, do the same depth yourself and say so.
## Autonomous Work Mode
When the user says `do work autonomously`, `work you can do autonomously`, `keep going`, or similar, do not stop after a queue summary or one local patch. Treat it as permission to process the eligible issue/PR queue sequentially until no safe autonomous item remains, each item is landed/closed/deferred with proof, or a blocker requires Peter.
Never work multiple tickets at once. For each item:
1. Read the issue/PR, related code, docs, CI, and `VISION.md` if present; Google/use official docs when facts may be stale or unclear.
2. Decide if it is autonomous:
- Go: performance improvements unless complexity rises too much; bugfixes with repro/root cause and verification path; small UI/UX tweaks; docs fixes; narrow test/internal fixes; low-risk dependency/CI cleanup with green proof.
- Ask first: new features, product/vision choices, broad behavior changes, risky dependencies, security-sensitive changes without strong proof, live-provider work without usable credentials, anything that cannot be end-to-end tested.
- Refactor preference: choose a clean bounded refactor when it is the better fix for an autonomous item; do not use "small patch" as the default if it leaves worse design.
3. Implement or fix the PR in the best maintainable way. Prefer updating the contributor PR when writable; otherwise recreate locally with credit.
4. Verify locally and live end-to-end when possible. For UI behavior, use the repo's expected live UI proof path, such as Peekaboo, browser-use, screenshots, or VM proof. For API/provider behavior, use a real usable key/account through the expected secret workflow when available. If access is missing, stop before pretending the item is done and ask Peter for help.
5. Run Codex Auto Review before commit/land unless trivial/docs-only or explicitly skipped; address accepted/actionable findings.
6. Ensure CI is green, PR description/changelog are good, land/close/comment with evidence, then return to `main`, pull `--ff-only`, and verify a clean worktree before selecting the next autonomous item.
7. After every landed PR, post a PR comment with exactly how it was tested: local commands, live/UI/API proof, CI run/check state, landed commit, and any caveats. If verification images apply, upload/post them with `gh image` when available; if the uploader is unavailable, say so and include the screenshot path or alternate GitHub attachment proof instead of silently omitting images.
Do not end autonomous mode with dirty files or an unpushed local fix unless blocked. If blocked, state the exact blocker, current branch/status, proof already gathered, and the next decision needed.
Autonomous work is still bounded by scope: current repo by default; broad/all queues only when the user asked for broad/all/everything or named owners/orgs.
## Trust Signals
Include author/opener trust for every non-maintainer item you recommend acting on. For low-risk Dependabot/internal items, a terse bot/internal trust line is enough.
Prefer the bundled helper:
```bash
skills/github-project-triage/scripts/github-activity.sh --repo <owner/repo> --global <login>
```
Fallback if this skill checkout lacks the helper:
```bash
~/Projects/clawdbot/.agents/skills/openclaw-pr-maintainer/scripts/github-activity.sh --repo <owner/repo> --global <login>
```
Also use `github-author-context` when a PR needs deeper trust judgment, especially for OpenClaw, security-sensitive changes, broad PRs, new accounts, or unusual author behavior. Prefer existing contributor notes first:
```bash
~/Projects/maintainers/scripts/clawtributors find github <login>
```
Trust output must stay factual:
```text
Trust: @login; acct 2021-04-03; repo 2 PRs/1 issue/0 commits in 12mo; GitHub 9 PRs/3 issues/12 reviews; signal: known contributor / new drive-by / bot / unknown.
```
Do not treat trust as proof. It changes review depth, not correctness.
## Item Evaluation
Classify each item:
- `bug`: require repro/log/failing test/current-main proof when feasible; identify root cause before recommending fix/merge.
- `feature`: require end-to-end test plan. If live validation needs a provider key, account, device, service, model access, or paid API, say exactly what credential/access is missing before work can be considered complete.
- `dependency`: explain package group, major/minor risk, failing checks, runtime/engine changes, and whether to split.
- `security`: raise priority, require careful code-path proof, tests, and trust/context; do not merge on rationale alone.
- `docs/internal`: lower risk, but still explain user-visible relevance and stale/generated churn risk.
Judge:
- `Fit`: good / mixed / poor, with one reason.
- `Risk`: low / medium / high, with blast radius.
- `Proof`: current CI, local repro, failing test, live E2E, or missing proof.
- `Blocker`: first-time contributor CI approval, failing check, missing key, unclear product direction, stale branch, untrusted/broad diff, no repro, conflicts.
- `Next`: approve CI, run test, request repro, split PR, patch locally, merge after green, close with proof, or defer.
## Fast Queue Map
Use this only when the scope is broad. Start with repo-level queue maps. This finds repos with open issues and/or PRs and gives counts.
PR queue, primary triage order:
```bash
repobar_cmd repos \
--scope all \
--only-with work \
--owner steipete \
--owner openclaw \
--sort prs \
--json
```
Issue pressure, second pass when issues matter:
```bash
repobar_cmd repos \
--scope all \
--only-with work \
--owner steipete \
--owner openclaw \
--sort issues \
--json
```
Use `--forks` and `--archived` only when the user says "all", "everything", or asks for archaeology. Default triage should omit forks and archived repos unless their queues are specifically relevant.
For a compact terminal view:
```bash
repobar_cmd repos --scope all --only-with work --owner steipete --owner openclaw --sort prs --plain
```
Useful `jq` summary:
```bash
repobar_cmd repos --scope all --only-with work --owner steipete --owner openclaw --sort prs --json |
jq -r '.[] | [.fullName, .openIssues, .openPulls, .activityTitle, .activityActor] | @tsv'
```
When summarizing a PR-sorted queue, preserve RepoBar's PR-count order. Do not include a lower-PR repo while omitting a higher-PR repo from the same owner scope. Zero-issue repos with open PRs, for example `openclaw/crabbox`, are still triage-relevant.
## Detail Pass
After a broad queue map, inspect only the top repos unless the user explicitly wants exhaustive detail.
```bash
repobar_cmd issues <owner/name> --limit 50 --json
repobar_cmd pulls <owner/name> --limit 50 --json
repobar_cmd ci <owner/name> --limit 20 --json
repobar_cmd activity <owner/name> --limit 20 --json
```
For PRs that look mergeable or suspicious, switch to `gh` for maintainer-grade state:
```bash
gh pr view <n> --repo <owner/name> --json number,title,state,author,isDraft,mergeStateStatus,reviewDecision,statusCheckRollup,updatedAt,url
gh pr diff <n> --repo <owner/name> --patch
gh run list --repo <owner/name> --branch <branch> --limit 10
```
For issues that may already be fixed, switch to `gh issue view`, then inspect current source before commenting or closing.
For OpenClaw/ClawdBot queues, use the OpenClaw maintainer pass when useful:
- search duplicates/related threads with `gitcrawl` if available;
- use the activity helper for opener/author identity;
- suppress top-maintainer noise unless the user asks for maintainer-owned work;
- prefer external/user-reported bugs and PRs with clear proof.
## Local Cross-Check
Use this when the task mentions local project state, dirty repos, or "what do I own here".
```bash
repobar_cmd local --root "$HOME/Projects" --depth 1 --limit 200 --plain
repobar_cmd local --root "$HOME/Projects" --depth 1 --sync --limit 200 --json
```
Do not run destructive local actions (`local reset`, branch deletes, checkout moves) unless the user explicitly asks.
## Triage Heuristics
Prioritize:
- PRs with green or nearly-green CI, recent maintainer activity, or low-risk dependency/docs/test changes.
- Repos with high open PR counts but recent activity, because they often hide obvious cleanup.
- Issues that are reproducible, recently reported, or block releases.
- Security, release, auth, install, CI, and data-loss reports before cosmetic items.
- Bugs with clear current-main reproduction and narrow owner path.
- Features only when live validation is possible or the missing access is explicit.
Deprioritize:
- Archived repos unless the user asked for them.
- Fork-only queues unless the fork is actively maintained by Peter.
- Old broad feature requests with no reproduction or owner signal.
- Repos with missing/removable remotes until local state is clarified.
- Feature/provider PRs that need unavailable API keys or accounts for end-to-end proof.
- Broad generated changes without a clear user problem, test plan, or trusted author signal.
## Output Shape
For current-project triage, answer with:
```text
Repo: owner/name
Source: gh list/view/diff/checks, local source/tests where inspected
Immediate:
- #123 PR: title
What: one-line summary in plain words.
Type/Fit/Risk: bug|feature|dependency; good|mixed|poor; low|medium|high because ...
Trust: @login; acct date; repo/global activity; known/unknown/bot.
Proof: CI/repro/test/e2e state.
Blocker: none / missing key / first-time CI approval / failing lint / unclear direction.
Next: exact maintainer action.
Needs judgment:
- #124 issue: ...
Defer/close:
- #125 issue: ...
Skipped:
- <why>
```
For a broad scan, answer with:
```text
Owners scanned: steipete, openclaw
Source: RepoBar <command summary>, plus gh for selected PRs/issues
Top queues:
- owner/repo: X issues, Y PRs; why it matters; next action
Immediate actions:
- <small obvious merge/fix/comment/rerun, with item summary>
Needs judgment:
- <larger/ambiguous queues, with item summary>
Skipped:
- archived/forks/missing access/etc.
```
When the user asks to act, keep going: inspect the selected PRs/issues with `gh`, rerun/fix CI, comment/close/merge only with evidence, and report exact commands/proof.
@@ -0,0 +1,4 @@
interface:
display_name: "GitHub Project Triage"
short_description: "Always use for triage; URL-first GitHub queue cards"
default_prompt: "Use $github-project-triage to triage the current GitHub repo: scan open issues and PRs, read comments, treat Peter/owner comments as authoritative, print URL-first autonomous candidates plus needs-Peter blockers, and only start work when explicitly asked. When autonomous work is requested, process eligible items one at a time through verification, autoreview, green CI, merge/closeout, post-merge proof comments with exact tests and images when applicable, and a clean checkout."
@@ -0,0 +1,177 @@
#!/usr/bin/env bash
set -euo pipefail
repo="openclaw/openclaw"
months="12"
include_global="0"
usage() {
printf 'Usage: %s [--repo owner/repo] [--months N] [--global] <github-login> [login...]\n' "$0"
}
die() {
printf 'error: %s\n' "$*" >&2
exit 1
}
need() {
command -v "$1" >/dev/null 2>&1 || die "missing required command: $1"
}
date_utc_relative_months() {
local count="$1"
if date -u -v-"${count}"m +%Y-%m-%dT00:00:00Z >/dev/null 2>&1; then
date -u -v-"${count}"m +%Y-%m-%dT00:00:00Z
return
fi
date -u -d "${count} months ago" +%Y-%m-%dT00:00:00Z
}
date_to_epoch() {
local value="$1"
if date -u -j -f '%Y-%m-%dT%H:%M:%SZ' "$value" +%s >/dev/null 2>&1; then
date -u -j -f '%Y-%m-%dT%H:%M:%SZ' "$value" +%s
return
fi
date -u -d "$value" +%s
}
rough_age() {
local created_at="$1"
local now_s created_s days
now_s=$(date -u +%s)
created_s=$(date_to_epoch "$created_at")
days=$(((now_s - created_s) / 86400))
if ((days < 120)); then
printf '~%dd old' "$days"
return
fi
awk -v days="$days" 'BEGIN { printf "~%.1fy old", days / 365.2425 }'
}
thread_kinds() {
local login="$1"
local since_ts="$2"
gh api --paginate "repos/${repo}/issues?state=all&creator=${login}&since=${since_ts}&per_page=100" \
--jq ".[] | select(.created_at >= \"${since_ts}\") | if has(\"pull_request\") then \"pr\" else \"issue\" end"
}
count_kind_lines() {
local kind="$1"
local lines="$2"
grep -cx "$kind" <<<"$lines" 2>/dev/null || true
}
count_commits() {
local login="$1"
local since_ts="$2"
gh api --paginate "repos/${repo}/commits?author=${login}&since=${since_ts}&per_page=100" \
--jq '.[].sha' | wc -l | tr -d '[:space:]'
}
global_activity() {
local login="$1"
local since_ts="$2"
local now_ts="$3"
gh api graphql \
-f login="$login" \
-f from="$since_ts" \
-f to="$now_ts" \
-f query='
query($login: String!, $from: DateTime!, $to: DateTime!) {
user(login: $login) {
contributionsCollection(from: $from, to: $to) {
totalCommitContributions
totalIssueContributions
totalPullRequestContributions
totalPullRequestReviewContributions
}
}
}' \
--jq '.data.user.contributionsCollection // empty'
}
while [[ $# -gt 0 ]]; do
case "$1" in
--repo)
[[ $# -ge 2 ]] || die "--repo requires owner/repo"
repo="$2"
shift 2
;;
--months)
[[ $# -ge 2 ]] || die "--months requires a positive integer"
months="$2"
[[ "$months" =~ ^[0-9]+$ && "$months" != "0" ]] || die "--months must be a positive integer"
shift 2
;;
--global)
include_global="1"
shift
;;
-h | --help)
usage
exit 0
;;
--)
shift
break
;;
-*)
die "unknown option: $1"
;;
*)
break
;;
esac
done
[[ $# -gt 0 ]] || {
usage >&2
exit 2
}
need gh
need jq
since_ts=$(date_utc_relative_months "$months")
now_ts=$(date -u +%Y-%m-%dT%H:00:00Z)
for login in "$@"; do
profile=$(gh api "users/${login}" --jq '{login,name,created_at,type}')
display_login=$(jq -r '.login' <<<"$profile")
name=$(jq -r '.name // empty' <<<"$profile")
created_at=$(jq -r '.created_at' <<<"$profile")
type=$(jq -r '.type' <<<"$profile")
created_day=${created_at%%T*}
kinds=$(thread_kinds "$display_login" "$since_ts")
prs=$(count_kind_lines pr "$kinds")
issues=$(count_kind_lines issue "$kinds")
commits=$(count_commits "$display_login" "$since_ts")
if [[ -n "$name" ]]; then
printf '%s (@%s, %s, account created %s, %s)\n' \
"$name" "$display_login" "$type" "$created_day" "$(rough_age "$created_at")"
else
printf '@%s (%s, account created %s, %s)\n' \
"$display_login" "$type" "$created_day" "$(rough_age "$created_at")"
fi
printf '%s last %smo: %s PRs, %s issues, %s commits\n' "$repo" "$months" "$prs" "$issues" "$commits"
if [[ "$include_global" == "1" ]]; then
if global_json=$(global_activity "$display_login" "$since_ts" "$now_ts" 2>/dev/null); then
if [[ -n "$global_json" ]]; then
global_commits=$(jq -r '.totalCommitContributions' <<<"$global_json")
global_issues=$(jq -r '.totalIssueContributions' <<<"$global_json")
global_prs=$(jq -r '.totalPullRequestContributions' <<<"$global_json")
global_reviews=$(jq -r '.totalPullRequestReviewContributions' <<<"$global_json")
printf 'GitHub public last %smo: %s commits, %s PRs, %s issues, %s reviews\n' \
"$months" "$global_commits" "$global_prs" "$global_issues" "$global_reviews"
else
printf 'GitHub public last %smo: unavailable\n' "$months"
fi
else
printf 'GitHub public last %smo: unavailable\n' "$months"
fi
fi
done
+7
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@@ -0,0 +1,7 @@
---
name: grill-me
description: A relentless interview to sharpen a plan or design.
disable-model-invocation: true
---
Run a `/grilling` session.
+10
View File
@@ -0,0 +1,10 @@
---
name: grilling
description: Interview the user relentlessly about a plan or design. Use when the user wants to stress-test a plan before building, or uses any 'grill' trigger phrases.
---
Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.
Ask the questions one at a time, waiting for feedback on each question before continuing. Asking multiple questions at once is bewildering.
If a question can be answered by exploring the codebase, explore the codebase instead.
+16
View File
@@ -0,0 +1,16 @@
---
name: handoff
description: Compact the current conversation into a handoff document for another agent to pick up.
argument-hint: "What will the next session be used for?"
disable-model-invocation: true
---
Write a handoff document summarising the current conversation so a fresh agent can continue the work. Save to the temporary directory of the user's OS - not the current workspace.
Include a "suggested skills" section in the document, which suggests skills that the agent should invoke.
Do not duplicate content already captured in other artifacts (PRDs, plans, ADRs, issues, commits, diffs). Reference them by path or URL instead.
Redact any sensitive information, such as API keys, passwords, or personally identifiable information.
If the user passed arguments, treat them as a description of what the next session will focus on and tailor the doc accordingly.