answer-reviewer-questi…
For each reviewer question on a PR, recall implementation reasoning and compose a raw answer. Use when the user asks to \"answer reviewer questions\", \"draft…
Scans an existing codebase and generates project-specific skills that capture inferred conventions such as naming, file organization, framework usage, data access, error handling, and testing style. Writes into the project's chosen skill directory (e.g., `.claude/skills/`,
$ npx -y skills add tobihagemann/turbo --skill create-project-skills --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/create-project-skillsContext preview
The summary Claude sees to decide when to auto-load this skill.
Scans an existing codebase and generates project-specific skills that capture inferred conventions such as naming, file organization, framework usage, data access, error handling, and testing style. Writes into the project's chosen skill directory (e.g., `.claude/skills/`,
name: create-project-skills description: "Scans an existing codebase and generates project-specific skills that capture inferred conventions such as naming, file organization, framework usage, data access, error handling, and testing style. Writes into the project's chosen skill directory (e.g., `.claude/skills/`, `.agents/skills/`, or a custom path). Use when the user asks to \"extract skills from the codebase\", \"create project skills\", \"infer project conventions as skills\", \"codify patterns as skills\", or \"mine the repo for best practices\"."
Generates one skill per detected convention area in the project's skill directory so future Claude or Codex sessions auto-load them when working in the repo.
At the start, use `TaskCreate` to create a task for each phase:
1. Survey codebase 2. Extract patterns in parallel 3. Evaluate patterns 4. Propose skill list 5. Run `/create-skill` skill
If `$ARGUMENTS` specifies paths, scope the scan to those paths; otherwise scan the whole repository.
Build the extraction context:
1. Detect primary languages and frameworks from manifest files (`package.json`, `Cargo.toml`, `pyproject.toml`, `go.mod`, `Package.swift`, `pom.xml`, `Gemfile`, and others appropriate to the stack). 2. Map the top-level source directory structure and note test directory conventions. 3. Read `CLAUDE.md`, `.claude/rules/`, `AGENTS.md`, and any `.cursor/rules` or `.cursorrules`. Note the conventions already documented there. The generated skills must not duplicate them. 4. Determine the target skill directory:
5. In the chosen target directory, list existing skills. For each, record the skill name, the description from SKILL.md frontmatter, and the first `##` section heading from the body. These signals feed rename-conflict detection in Step 3.
Output a short text summary of detected stack, top-level layout, chosen target directory, and existing skills before moving on.
When that summary shows no source code to extract conventions from, stop here rather than dispatching Step 2. Executable code in any language qualifies, including scripts no manifest declares, so judge from the directory map rather than the detected stack. Documentation, instruction files, and configuration alone do not: extraction run over prose returns that prose's assertions as observed conventions, and Step 3 scores them with no code sites to test them against.
State that as text first — what the survey found, and that conventions extracted from it would have nothing to verify against. Then use `AskUserQuestion` to offer:
On the first option, run the `/create-skill` skill directly on that knowledge and skip the remaining steps. On either of the first two, mark the extraction phases cancelled so they no longer read as pending work.
Read [references/pattern-extractor.md](references/pattern-extractor.md) to see the full taxonomy of pattern categories. Decide which categories apply to the detected stack (e.g., drop "Styling and UI" for a backend service, drop "State management" for a static-analysis tool).
Emit all extraction Agent tool calls below in one assistant message. Each Agent call uses `model: "opus"` and no `name`. Wait for every agent to report before continuing. Do not begin the next step on a partial set, and do not relaunch an agent that has not yet reported. Launch one Agent per applicable category and state the total count explicitly when emitting the calls. Every agent's prompt must direct it to treat the shared working tree and its git index as read-only and to extract by reading and reasoning. HEAD stays where it is: read other refs with `git show <ref>:<path>` rather than `git checkout` or `git switch`. Each agent's prompt must:
Aggregate findings from all agents. For each finding, score three axes:
Group the surviving findings by topic into candidate skills.
A composable dev process for agentic coding harnesses, packaged as modular skills. Turbo has sibling editions for Claude Code and Codex. The Claude Code edition is production-tested.
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