690503:0135 Update workflow #01
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---
name: diagnose
description: Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.
---
# Diagnose
A discipline for hard bugs. Skip phases only when explicitly justified.
When exploring the codebase, use the project's domain glossary 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 fast, deterministic, agent-runnable pass/fail signal for the bug, you will find the cause — bisection, hypothesis-testing, and instrumentation all just consume that signal. 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.
### Iterate on the loop itself
Treat the loop as a product. Once you have _a_ loop, ask:
- 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 loop is 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.
Do not proceed to Phase 2 until you have a loop you believe in.
## Phase 2 — Reproduce
Run the loop. Watch the bug appear.
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.
Do not proceed until you reproduce the bug.
## 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"
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# ADR Format
ADRs live in `docs/adr/` and use sequential numbering: `0001-slug.md`, `0002-slug.md`, etc.
Create the `docs/adr/` directory lazily — only when the first ADR is needed.
## Template
```md
# {Short title of the decision}
{1-3 sentences: what's the context, what did we decide, and why.}
```
That's it. An ADR can be a single paragraph. The value is in recording *that* a decision was made and *why* — not in filling out sections.
## Optional sections
Only include these when they add genuine value. Most ADRs won't need them.
- **Status** frontmatter (`proposed | accepted | deprecated | superseded by ADR-NNNN`) — useful when decisions are revisited
- **Considered Options** — only when the rejected alternatives are worth remembering
- **Consequences** — only when non-obvious downstream effects need to be called out
## Numbering
Scan `docs/adr/` for the highest existing number and increment by one.
## When to offer an ADR
All three of these must be true:
1. **Hard to reverse** — the cost of changing your mind later is meaningful
2. **Surprising without context** — a future reader will look at the code and wonder "why on earth did they do it this way?"
3. **The result of a real trade-off** — there were genuine alternatives and you picked one for specific reasons
If a decision is easy to reverse, skip it — you'll just reverse it. If it's not surprising, nobody will wonder why. If there was no real alternative, there's nothing to record beyond "we did the obvious thing."
### What qualifies
- **Architectural shape.** "We're using a monorepo." "The write model is event-sourced, the read model is projected into Postgres."
- **Integration patterns between contexts.** "Ordering and Billing communicate via domain events, not synchronous HTTP."
- **Technology choices that carry lock-in.** Database, message bus, auth provider, deployment target. Not every library — just the ones that would take a quarter to swap out.
- **Boundary and scope decisions.** "Customer data is owned by the Customer context; other contexts reference it by ID only." The explicit no-s are as valuable as the yes-s.
- **Deliberate deviations from the obvious path.** "We're using manual SQL instead of an ORM because X." Anything where a reasonable reader would assume the opposite. These stop the next engineer from "fixing" something that was deliberate.
- **Constraints not visible in the code.** "We can't use AWS because of compliance requirements." "Response times must be under 200ms because of the partner API contract."
- **Rejected alternatives when the rejection is non-obvious.** If you considered GraphQL and picked REST for subtle reasons, record it — otherwise someone will suggest GraphQL again in six months.
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# CONTEXT.md Format
## Structure
```md
# {Context Name}
{One or two sentence description of what this context is and why it exists.}
## Language
**Order**:
{A concise description of the term}
_Avoid_: Purchase, transaction
**Invoice**:
A request for payment sent to a customer after delivery.
_Avoid_: Bill, payment request
**Customer**:
A person or organization that places orders.
_Avoid_: Client, buyer, account
## Relationships
- An **Order** produces one or more **Invoices**
- An **Invoice** belongs to exactly one **Customer**
## Example dialogue
> **Dev:** "When a **Customer** places an **Order**, do we create the **Invoice** immediately?"
> **Domain expert:** "No — an **Invoice** is only generated once a **Fulfillment** is confirmed."
## Flagged ambiguities
- "account" was used to mean both **Customer** and **User** — resolved: these are distinct concepts.
```
## Rules
- **Be opinionated.** When multiple words exist for the same concept, pick the best one and list the others as aliases to avoid.
- **Flag conflicts explicitly.** If a term is used ambiguously, call it out in "Flagged ambiguities" with a clear resolution.
- **Keep definitions tight.** One sentence max. Define what it IS, not what it does.
- **Show relationships.** Use bold term names and express cardinality where obvious.
- **Only include terms specific to this project's context.** General programming concepts (timeouts, error types, utility patterns) don't belong even if the project uses them extensively. Before adding a term, ask: is this a concept unique to this context, or a general programming concept? Only the former belongs.
- **Group terms under subheadings** when natural clusters emerge. If all terms belong to a single cohesive area, a flat list is fine.
- **Write an example dialogue.** A conversation between a dev and a domain expert that demonstrates how the terms interact naturally and clarifies boundaries between related concepts.
## Single vs multi-context repos
**Single context (most repos):** One `CONTEXT.md` at the repo root.
**Multiple contexts:** A `CONTEXT-MAP.md` at the repo root lists the contexts, where they live, and how they relate to each other:
```md
# Context Map
## Contexts
- [Ordering](./src/ordering/CONTEXT.md) — receives and tracks customer orders
- [Billing](./src/billing/CONTEXT.md) — generates invoices and processes payments
- [Fulfillment](./src/fulfillment/CONTEXT.md) — manages warehouse picking and shipping
## Relationships
- **Ordering → Fulfillment**: Ordering emits `OrderPlaced` events; Fulfillment consumes them to start picking
- **Fulfillment → Billing**: Fulfillment emits `ShipmentDispatched` events; Billing consumes them to generate invoices
- **Ordering ↔ Billing**: Shared types for `CustomerId` and `Money`
```
The skill infers which structure applies:
- If `CONTEXT-MAP.md` exists, read it to find contexts
- If only a root `CONTEXT.md` exists, single context
- If neither exists, create a root `CONTEXT.md` lazily when the first term is resolved
When multiple contexts exist, infer which one the current topic relates to. If unclear, ask.
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---
name: grill-with-docs
description: Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.
---
<what-to-do>
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.
If a question can be answered by exploring the codebase, explore the codebase instead.
</what-to-do>
<supporting-info>
## Domain awareness
During codebase exploration, also look for existing documentation:
### File structure
Most repos have a single context:
```
/
├── CONTEXT.md
├── docs/
│ └── adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
```
If a `CONTEXT-MAP.md` exists at the root, the repo has multiple contexts. The map points to where each one lives:
```
/
├── CONTEXT-MAP.md
├── docs/
│ └── adr/ ← system-wide decisions
├── src/
│ ├── ordering/
│ │ ├── CONTEXT.md
│ │ └── docs/adr/ ← context-specific decisions
│ └── billing/
│ ├── CONTEXT.md
│ └── docs/adr/
```
Create files lazily — only when you have something to write. If no `CONTEXT.md` exists, create one when the first term is resolved. If no `docs/adr/` exists, create it when the first ADR is needed.
## During the session
### Challenge against the glossary
When the user uses a term that conflicts with the existing language in `CONTEXT.md`, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"
### Sharpen fuzzy language
When the user uses vague or overloaded terms, propose a precise canonical term. "You're saying 'account' — do you mean the Customer or the User? Those are different things."
### Discuss concrete scenarios
When domain relationships are being discussed, stress-test them with specific scenarios. Invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts.
### Cross-reference with code
When the user states how something works, check whether the code agrees. If you find a contradiction, surface it: "Your code cancels entire Orders, but you just said partial cancellation is possible — which is right?"
### Update CONTEXT.md inline
When a term is resolved, update `CONTEXT.md` right there. Don't batch these up — capture them as they happen. Use the format in [CONTEXT-FORMAT.md](./CONTEXT-FORMAT.md).
Don't couple `CONTEXT.md` to implementation details. Only include terms that are meaningful to domain experts.
### Offer ADRs sparingly
Only offer to create an ADR when all three are true:
1. **Hard to reverse** — the cost of changing your mind later is meaningful
2. **Surprising without context** — a future reader will wonder "why did they do it this way?"
3. **The result of a real trade-off** — there were genuine alternatives and you picked one for specific reasons
If any of the three is missing, skip the ADR. Use the format in [ADR-FORMAT.md](./ADR-FORMAT.md).
</supporting-info>
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---
name: setup-matt-pocock-skills
description: Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local markdown), triage label vocabulary, and domain doc layout. Run before first use of `to-issues`, `to-prd`, `triage`, `diagnose`, `tdd`, `improve-codebase-architecture`, or `zoom-out` — or if those skills appear to be missing context about the issue tracker, triage labels, or domain docs.
disable-model-invocation: true
---
# Setup Matt Pocock's Skills
Scaffold the per-repo configuration that the engineering skills assume:
- **Issue tracker** — where issues live (GitHub by default; local markdown is also supported out of the box)
- **Triage labels** — the strings used for the five canonical triage roles
- **Domain docs** — where `CONTEXT.md` and ADRs live, and the consumer rules for reading them
This is a prompt-driven skill, not a deterministic script. Explore, present what you found, confirm with the user, then write.
## Process
### 1. Explore
Look at the current repo to understand its starting state. Read whatever exists; don't assume:
- `git remote -v` and `.git/config` — is this a GitHub repo? Which one?
- `AGENTS.md` and `CLAUDE.md` at the repo root — does either exist? Is there already an `## Agent skills` section in either?
- `CONTEXT.md` and `CONTEXT-MAP.md` at the repo root
- `docs/adr/` and any `src/*/docs/adr/` directories
- `docs/agents/` — does this skill's prior output already exist?
- `.scratch/` — sign that a local-markdown issue tracker convention is already in use
### 2. Present findings and ask
Summarise what's present and what's missing. Then walk the user through the three decisions **one at a time** — present a section, get the user's answer, then move to the next. Don't dump all three at once.
Assume the user does not know what these terms mean. Each section starts with a short explainer (what it is, why these skills need it, what changes if they pick differently). Then show the choices and the default.
**Section A — Issue tracker.**
> Explainer: The "issue tracker" is where issues live for this repo. Skills like `to-issues`, `triage`, `to-prd`, and `qa` read from and write to it — they need to know whether to call `gh issue create`, write a markdown file under `.scratch/`, or follow some other workflow you describe. Pick the place you actually track work for this repo.
Default posture: these skills were designed for GitHub. If a `git remote` points at GitHub, propose that. If a `git remote` points at GitLab (`gitlab.com` or a self-hosted host), propose GitLab. Otherwise (or if the user prefers), offer:
- **GitHub** — issues live in the repo's GitHub Issues (uses the `gh` CLI)
- **GitLab** — issues live in the repo's GitLab Issues (uses the [`glab`](https://gitlab.com/gitlab-org/cli) CLI)
- **Local markdown** — issues live as files under `.scratch/<feature>/` in this repo (good for solo projects or repos without a remote)
- **Other** (Jira, Linear, etc.) — ask the user to describe the workflow in one paragraph; the skill will record it as freeform prose
**Section B — Triage label vocabulary.**
> Explainer: When the `triage` skill processes an incoming issue, it moves it through a state machine — needs evaluation, waiting on reporter, ready for an AFK agent to pick up, ready for a human, or won't fix. To do that, it needs to apply labels (or the equivalent in your issue tracker) that match strings *you've actually configured*. If your repo already uses different label names (e.g. `bug:triage` instead of `needs-triage`), map them here so the skill applies the right ones instead of creating duplicates.
The five canonical roles:
- `needs-triage` — maintainer needs to evaluate
- `needs-info` — waiting on reporter
- `ready-for-agent` — fully specified, AFK-ready (an agent can pick it up with no human context)
- `ready-for-human` — needs human implementation
- `wontfix` — will not be actioned
Default: each role's string equals its name. Ask the user if they want to override any. If their issue tracker has no existing labels, the defaults are fine.
**Section C — Domain docs.**
> Explainer: Some skills (`improve-codebase-architecture`, `diagnose`, `tdd`) read a `CONTEXT.md` file to learn the project's domain language, and `docs/adr/` for past architectural decisions. They need to know whether the repo has one global context or multiple (e.g. a monorepo with separate frontend/backend contexts) so they look in the right place.
Confirm the layout:
- **Single-context** — one `CONTEXT.md` + `docs/adr/` at the repo root. Most repos are this.
- **Multi-context** — `CONTEXT-MAP.md` at the root pointing to per-context `CONTEXT.md` files (typically a monorepo).
### 3. Confirm and edit
Show the user a draft of:
- The `## Agent skills` block to add to whichever of `CLAUDE.md` / `AGENTS.md` is being edited (see step 4 for selection rules)
- The contents of `docs/agents/issue-tracker.md`, `docs/agents/triage-labels.md`, `docs/agents/domain.md`
Let them edit before writing.
### 4. Write
**Pick the file to edit:**
- If `CLAUDE.md` exists, edit it.
- Else if `AGENTS.md` exists, edit it.
- If neither exists, ask the user which one to create — don't pick for them.
Never create `AGENTS.md` when `CLAUDE.md` already exists (or vice versa) — always edit the one that's already there.
If an `## Agent skills` block already exists in the chosen file, update its contents in-place rather than appending a duplicate. Don't overwrite user edits to the surrounding sections.
The block:
```markdown
## Agent skills
### Issue tracker
[one-line summary of where issues are tracked]. See `docs/agents/issue-tracker.md`.
### Triage labels
[one-line summary of the label vocabulary]. See `docs/agents/triage-labels.md`.
### Domain docs
[one-line summary of layout — "single-context" or "multi-context"]. See `docs/agents/domain.md`.
```
Then write the three docs files using the seed templates in this skill folder as a starting point:
- [issue-tracker-github.md](./issue-tracker-github.md) — GitHub issue tracker
- [issue-tracker-gitlab.md](./issue-tracker-gitlab.md) — GitLab issue tracker
- [issue-tracker-local.md](./issue-tracker-local.md) — local-markdown issue tracker
- [triage-labels.md](./triage-labels.md) — label mapping
- [domain.md](./domain.md) — domain doc consumer rules + layout
For "other" issue trackers, write `docs/agents/issue-tracker.md` from scratch using the user's description.
### 5. Done
Tell the user the setup is complete and which engineering skills will now read from these files. Mention they can edit `docs/agents/*.md` directly later — re-running this skill is only necessary if they want to switch issue trackers or restart from scratch.
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# Domain Docs
How the engineering skills should consume this repo's domain documentation when exploring the codebase.
## Before exploring, read these
- **`CONTEXT.md`** at the repo root, or
- **`CONTEXT-MAP.md`** at the repo root if it exists — it points at one `CONTEXT.md` per context. Read each one relevant to the topic.
- **`docs/adr/`** — read ADRs that touch the area you're about to work in. In multi-context repos, also check `src/<context>/docs/adr/` for context-scoped decisions.
If any of these files don't exist, **proceed silently**. Don't flag their absence; don't suggest creating them upfront. The producer skill (`/grill-with-docs`) creates them lazily when terms or decisions actually get resolved.
## File structure
Single-context repo (most repos):
```
/
├── CONTEXT.md
├── docs/adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
```
Multi-context repo (presence of `CONTEXT-MAP.md` at the root):
```
/
├── CONTEXT-MAP.md
├── docs/adr/ ← system-wide decisions
└── src/
├── ordering/
│ ├── CONTEXT.md
│ └── docs/adr/ ← context-specific decisions
└── billing/
├── CONTEXT.md
└── docs/adr/
```
## Use the glossary's vocabulary
When your output names a domain concept (in an issue title, a refactor proposal, a hypothesis, a test name), use the term as defined in `CONTEXT.md`. Don't drift to synonyms the glossary explicitly avoids.
If the concept you need isn't in the glossary yet, that's a signal — either you're inventing language the project doesn't use (reconsider) or there's a real gap (note it for `/grill-with-docs`).
## Flag ADR conflicts
If your output contradicts an existing ADR, surface it explicitly rather than silently overriding:
> _Contradicts ADR-0007 (event-sourced orders) — but worth reopening because…_
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# Issue tracker: GitHub
Issues and PRDs for this repo live as GitHub issues. Use the `gh` CLI for all operations.
## Conventions
- **Create an issue**: `gh issue create --title "..." --body "..."`. Use a heredoc for multi-line bodies.
- **Read an issue**: `gh issue view <number> --comments`, filtering comments by `jq` and also fetching labels.
- **List issues**: `gh issue list --state open --json number,title,body,labels,comments --jq '[.[] | {number, title, body, labels: [.labels[].name], comments: [.comments[].body]}]'` with appropriate `--label` and `--state` filters.
- **Comment on an issue**: `gh issue comment <number> --body "..."`
- **Apply / remove labels**: `gh issue edit <number> --add-label "..."` / `--remove-label "..."`
- **Close**: `gh issue close <number> --comment "..."`
Infer the repo from `git remote -v``gh` does this automatically when run inside a clone.
## When a skill says "publish to the issue tracker"
Create a GitHub issue.
## When a skill says "fetch the relevant ticket"
Run `gh issue view <number> --comments`.
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# Issue tracker: GitLab
Issues and PRDs for this repo live as GitLab issues. Use the [`glab`](https://gitlab.com/gitlab-org/cli) CLI for all operations.
## Conventions
- **Create an issue**: `glab issue create --title "..." --description "..."`. Use a heredoc for multi-line descriptions. Pass `--description -` to open an editor.
- **Read an issue**: `glab issue view <number> --comments`. Use `-F json` for machine-readable output.
- **List issues**: `glab issue list --state opened -F json` with appropriate `--label` filters. Note that GitLab uses `opened` (not `open`) for the state value.
- **Comment on an issue**: `glab issue note <number> --message "..."`. GitLab calls comments "notes".
- **Apply / remove labels**: `glab issue update <number> --label "..."` / `--unlabel "..."`. Multiple labels can be comma-separated or by repeating the flag.
- **Close**: `glab issue close <number>`. `glab issue close` does not accept a closing comment, so post the explanation first with `glab issue note <number> --message "..."`, then close.
- **Merge requests**: GitLab calls PRs "merge requests". Use `glab mr create`, `glab mr view`, `glab mr note`, etc. — the same shape as `gh pr ...` with `mr` in place of `pr` and `note`/`--message` in place of `comment`/`--body`.
Infer the repo from `git remote -v``glab` does this automatically when run inside a clone.
## When a skill says "publish to the issue tracker"
Create a GitLab issue.
## When a skill says "fetch the relevant ticket"
Run `glab issue view <number> --comments`.
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# Issue tracker: Local Markdown
Issues and PRDs for this repo live as markdown files in `.scratch/`.
## Conventions
- One feature per directory: `.scratch/<feature-slug>/`
- The PRD is `.scratch/<feature-slug>/PRD.md`
- Implementation issues are `.scratch/<feature-slug>/issues/<NN>-<slug>.md`, numbered from `01`
- Triage state is recorded as a `Status:` line near the top of each issue file (see `triage-labels.md` for the role strings)
- Comments and conversation history append to the bottom of the file under a `## Comments` heading
## When a skill says "publish to the issue tracker"
Create a new file under `.scratch/<feature-slug>/` (creating the directory if needed).
## When a skill says "fetch the relevant ticket"
Read the file at the referenced path. The user will normally pass the path or the issue number directly.
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# Triage Labels
The skills speak in terms of five canonical triage roles. This file maps those roles to the actual label strings used in this repo's issue tracker.
| Label in mattpocock/skills | Label in our tracker | Meaning |
| -------------------------- | -------------------- | ---------------------------------------- |
| `needs-triage` | `needs-triage` | Maintainer needs to evaluate this issue |
| `needs-info` | `needs-info` | Waiting on reporter for more information |
| `ready-for-agent` | `ready-for-agent` | Fully specified, ready for an AFK agent |
| `ready-for-human` | `ready-for-human` | Requires human implementation |
| `wontfix` | `wontfix` | Will not be actioned |
When a skill mentions a role (e.g. "apply the AFK-ready triage label"), use the corresponding label string from this table.
Edit the right-hand column to match whatever vocabulary you actually use.
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