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/runnpx skills add qwerfunch/cladding --skill rungit 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 | $0.00078 | $0.00736 |
| Opus 5 | $0.00039 | $0.00368 |
| Sonnet 5 | $0.00016 | $0.00147 |
| Haiku 4.5 | $0.00008 | $0.00074 |
Grade A, and why
run 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.
What it actually says
Cladding run (formerly drive)
Run clad run from the project root. The autonomous loop:
- Pre-flight
adapter.healthCheck()— fails fast on missing credentials or unreachable host. - For each ready feature (status
planned,depends_onsatisfied):- Specialist dispatch authors the implementation.
- Apply mutations to the working tree.
- L1 gates: Type / Lint / Arch.
- Reviewer dispatch —
HUMAN_REQUIREDhalt if reviewer identity equals specialist (anti-self-cert barrier). - UAT requires a human-pass evidence entry; missing →
HUMAN_REQUIREDhalt.
- Halt class is one of the 13 enumerated reasons (
ALL_FEATURES_DONE,MAX_ITERATIONS,WALL_CLOCK,BUDGET_EXCEEDED,BLOCKED_FEATURE,RETRY_THRESHOLD,GATE_NO_PROGRESS,HUMAN_REQUIRED,TRANSPORT_AUTH_FAILED,TRANSPORT_RATE_LIMITED,TRANSPORT_NETWORK,LLM_UNAVAILABLE,UNCAUGHT_ERROR).
Budget flags: --max-iterations, --max-wall-clock-ms, --max-retries. --cwd <path> targets a project directory other than the current one. --json emits the raw Iron Core result; default is the plain Soft Shell summary.
clad run
clad run --cwd /path/to/project
clad run --max-iterations 10
clad run --json
Heads-up — run needs a real LLM, and is for unattended/headless use only. The host AI (Claude Code, Cursor, …) drives work naturally in-session; clad run is the entry point for the opposite case — autonomous, no-human-in-the-loop progress (CI/cron/SDK). Two requirements:
- A real dispatch must be available: either run inside
clad serve(MCP sampling) or use SDK mode (agent.mode = sdk+ an API key). With neither, the loop falls back to the Mock transport and produces empty module stubs, not real implementations — yet still reports a normal halt. Treat a standaloneclad runwith no MCP server and no SDK key as not doing real work; verify withclad doctorafterward (a deterministic/Mock run is a red flag, not success). runmodifies the working tree.
Known gap (tracked): standalone
runon the Mock fallback should hard-fail withLLM_UNAVAILABLErather than silently stubbing. That change reconciles the adapterhealthCheckparity contract (F-049 AC-089, which currently treats the Mock fallback as "ready") and is a deliberate follow-up, not yet shipped.
After a run session, run clad doctor over the same --cwd to confirm the LLM dispatcher behaved — any sentinel_miss events surface as a health summary so you can tell whether the loop ran with full LLM refinement or fell back to deterministic per-artifact.
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 · 35 lines · 78 tokens per session scan A 9f95ff17d70c
run is a skill published in the GitHub repository qwerfunch/cladding (14 stars, last pushed 4d ago), licensed MIT. It adds 78 tokens to every session and 736 once invoked, about $0.0004 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.