cladding-init
Use only when the user explicitly names Cladding and asks to initialize, adopt, or refresh it; never use for an ordinary project creation or implementation…
Use only when the user explicitly names Cladding and asks to initialize, adopt, or refresh it; never use for an ordinary project creation or implementation request. Scaffold from an idea, planning document, or existing project through the MCP prepare/apply flow.
$ npx -y skills add qwerfunch/cladding --skill init --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/initContext preview
The summary Claude sees to decide when to auto-load this skill.
Use only when the user explicitly names Cladding and asks to initialize, adopt, or refresh it; never use for an ordinary project creation or implementation request. Scaffold from an idea, planning document, or existing project through the MCP prepare/apply flow.
name: init description: Use only when the user explicitly names Cladding and asks to initialize, adopt, or refresh it; never use for an ordinary project creation or implementation request. Scaffold from an idea, planning document, or existing project through the MCP prepare/apply flow.
Use this workflow only when the user explicitly asks to initialize, adopt, or refresh Cladding. Opening a repository alone is not consent to initialize it.
If the current user message itself matches `APPLY CLADDING XXXXXX`, do not call prepare or stage again. Call `clad_init` once and copy the entire user message, including the `APPLY CLADDING` prefix, into `confirmation`.
1. If a greenfield request has no project intent, ask for one short description. 2. Call `clad_prepare_init` with exactly one starting mode:
3. Read the returned prompt and observations. Draft the structured object required by `clad_init` using the current host model, then call `clad_stage_init` with the preparation token and that draft. Staging validates the draft and stores only ignored runtime state under `.cladding/host/`; it does not modify authored project files. 4. Show `plannedChanges`, the staged `confirmationQuestion`, and its one-time `approvalChallenge` to the user, then stop and wait for a separate reply. The original initialization request is not confirmation. 5. Only when the user's separate reply exactly matches `approvalChallenge`, call `clad_init` with the entire reply verbatim as `confirmation`—never strip the `APPLY CLADDING` prefix. Include the draft and token when the host retained them; process-per-turn hosts may omit both because Cladding resolves the exact staged draft from its short-lived machine-local cache. Questions, paraphrases, and generic acknowledgements are not approval. 6. If `nextQuestion` is present, show it verbatim and end the assistant turn immediately. Never answer it, infer an answer, or call either clarify tool during the initialization-approval turn. Continue with the Cladding clarify workflow only after a new user message supplies the answer. If no question remains, report that onboarding is complete and that the next step is to author the first feature's spec — its acceptance criteria and the files it will cover — before writing any code; the feature cycle starts there, not with scaffolding.
Do not run `clad init` in a shell from an AI-host onboarding session. Do not use MCP sampling. If the MCP tools are absent, tell the user to run `clad setup`, restart the AI host in the project directory, and stop without writing project files.
`clad_prepare_init` does not modify the workspace, and `clad_stage_init` writes only ignored runtime state. Never call stage and apply in the same assistant turn. Only `clad_init` writes authored artifacts, after explicit user confirmation plus schema and freshness validation. A stale, malformed, or replayed apply request must be prepared again.
Initialization also creates or appends `spec/index.yaml merge=union` in `.gitattributes`. It preserves every existing attribute and never assigns a merge driver to `spec/attestation.yaml`; the strict gate rewrites that verification record canonically after an ordinary merge.
The raw CLI remains available for terminal, CI, offline, and explicitly configured SDK automation; it is not the primary host onboarding path.
For an organization to trust AI with its code, three things must hold — trust, traceability, and stability at scale. cladding wraps your AI coding agent: your intent goes in before it writes, and the result is verified against your spec after, so those three are earned, not assumed. First L4 implementation of the Ironclad standard.
Repo: qwerfunch/cladding
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