一键导入
to-prd
Turn the current conversation context into a PRD and publish it to the project issue tracker. Use when user wants to create a PRD from the current context.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Turn the current conversation context into a PRD and publish it to the project issue tracker. Use when user wants to create a PRD from the current context.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Scaffold a new golden case for @butler/evals — validate and append the case to golden.jsonl, re-capture the baseline, and confirm the eval gate still passes. Use when a real agent failure or escaped bug should become a regression benchmark.
Work the Butler ready-for-agent issue queue in priority order — select the highest-priority unblocked issue (P0 > P1 > P2) and run /implement-issue on it, looping up to a per-run cap. Use ONLY when explicitly asked to "work the queue" / "implement the next issue(s)", or when fired by the scheduled routine. Do not auto-run.
Break a plan, spec, or PRD into independently-grabbable issues on the project issue tracker using tracer-bullet vertical slices. Use when user wants to convert a plan into issues, create implementation tickets, or break down work into issues.
End-to-end implementation of a GitHub issue — from reading the issue through TDD, code review, PR creation, CI monitoring, and merge. Use when the user says "implement issue
Phase 9 retrospective — read a window or set of recently-merged PRs, classify each harness/run finding with the eval-failure taxonomy, and append tagged learnings to docs/retro/learnings.md. Propose-only — writes ONLY under docs/retro/. Use when explicitly asked to "run a retrospective", "retro the last N PRs", or to review a batch of merged work for harness lessons. Do not auto-run.
Triage issues through a state machine driven by triage roles. Use when user wants to create an issue, triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.
| name | to-prd |
| description | Turn the current conversation context into a PRD and publish it to the project issue tracker. Use when user wants to create a PRD from the current context. |
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.
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.
Sketch out the major modules you will need to build or modify to complete the implementation. Actively look for opportunities to extract deep modules that can be tested in isolation.
A deep module (as opposed to a shallow module) is one which encapsulates a lot of functionality in a simple, testable interface which rarely changes.
Check with the user that these modules match their expectations. Check with the user which modules they want tests written for.
ready-for-agent triage label and a default P2 priority label — this immediately makes the PRD eligible for the AFK queue without requiring a human to hand-label it first. If the conversation context makes it clear this work is more urgent (e.g. an unblocking fix or a security issue), use P1 or P0 instead. The human can always override the priority after publishing.The problem that the user is facing, from the user's perspective.
The solution to the problem, from the user's perspective.
A LONG, numbered list of user stories. Each user story should be in the format of:
This list of user stories should be extremely extensive and cover all aspects of the feature.
A list of implementation decisions that were made. This can include:
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.
A list of testing decisions that were made. Include:
A description of the things that are out of scope for this PRD.
Any further notes about the feature.