Skills/to-prd/SKILL.md
Turn the current conversation context into a PRD and submit it as a GitHub issue. Use when user wants to create a PRD from the current context.
npx skillsauth add sammcj/agentic-coding to-prdInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
needs-triage triage label so it enters the normal triage flow.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 They may end up being outdated very quickly.
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.
</prd-template>development
Use when answering questions from this machine-learning knowledge base. Triggers: questions about transformers, attention cost and efficiency, and long-context scaling; 'what do we know about attention', 'check the ML wiki'. Read-only querying of compiled knowledge; to add, update, supersede, lint, or audit, use the llm-wiki skill instead.
development
Use when building or maintaining a self-contained personal knowledge base (an LLM wiki) as plain markdown, optionally opened as an Obsidian vault. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki health, auditing article claims against their sources, superseding stale knowledge, 'add to wiki', or any mention of 'LLM wiki' or 'Karpathy wiki'.
tools
Provides guidance and tools for hardware design. Activate when using KiCAD, looking up electronic parts or designing PCBs.
testing
Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise.