Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/qwerfunch/cladding/cladding-initnpx skills add qwerfunch/cladding --skill cladding-initgit clone --depth 1 https://github.com/qwerfunch/claddingWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00054 | $0.00649 |
| Opus 5 | $0.00027 | $0.00324 |
| Sonnet 5 | $0.00011 | $0.00130 |
| Haiku 4.5 | $0.00005 | $0.00065 |
Grade A, and why
cladding-init scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cladding init
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.
Required host workflow
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.
- If a greenfield request has no project intent, ask for one short description.
- Call
clad_prepare_initwith exactly one starting mode:ideawith the user's description.documentwith a project-relative planning-document path.existingfor an existing codebase; include an optional adoption goal.
- Read the returned prompt and observations. Draft the structured object required by
clad_initusing the current host model, then callclad_stage_initwith 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. - Show
plannedChanges, the stagedconfirmationQuestion, and its one-timeapprovalChallengeto the user, then stop and wait for a separate reply. The original initialization request is not confirmation. - Only when the user's separate reply exactly matches
approvalChallenge, callclad_initwith the entire reply verbatim asconfirmation—never strip theAPPLY CLADDINGprefix. 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. - If
nextQuestionis 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 ordinary development can begin.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 29 lines · 54 tokens per session scan A 6b4a9955697a
cladding-init is a skill published in the GitHub repository qwerfunch/cladding (14 stars, last pushed 4d ago), licensed MIT. It adds 54 tokens to every session and 649 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
map-plan
ARCHITECT phase - decompose complex tasks into atomic subtasks with research, spec, and branch-scoped plan artifacts under .map.
map-review
Interactive 4-section code review using monitor, predictor, and evaluator agents plus the user and maintainer role reviewers on current changes. Use when reviewing a diff, PR, or staged work before merge. Do NOT use to plan or implement; use map-plan or map-efficient.
map-debug
Structured MAP debugging via task-decomposer, actor, and monitor agents. Use when reproducing a bug, isolating a regression, or diagnosing an error with specialized agents — including failing or flaky tests (pytest AssertionError), crashes and segmentation faults, memory-corruption or memory errors in native/C…
map-learn
Capture reusable lessons after a completed MAP workflow. Use when a MAP run has finished and you want rules written to .claude/rules/learned/ from a workflow summary or handoff. Do NOT use during active implementation.
map-efficient
State-machine MAP execution workflow for Codex. Use when implementing an approved MAP plan end to end, resuming from branch MAP taskplan or stepstate.json artifacts, or running non-trivial multi-subtask work. Use map-fast for tiny one-shot edits.
map-task
Execute a single subtask from an existing MAP plan via Actor and Monitor. Use when map-plan has decomposed work and you want fine-grained control over one subtask. Do NOT use without an existing plan; run map-plan first.