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/doctornpx skills add qwerfunch/cladding --skill doctorgit 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 | $0.00093 | $0.00856 |
| Opus 5 | $0.00046 | $0.00428 |
| Sonnet 5 | $0.00019 | $0.00171 |
| Haiku 4.5 | $0.00009 | $0.00086 |
Grade A, and why
doctor 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cladding doctor
Run clad doctor from the project root. The verb is observability — it never mutates the working tree.
--cwd <path>— read events from a project directory other than the current one (default cwd).--json— emit the rawDoctorReportshape instead of the formatted text surface; the additive shape ({cwd, events, sentinelMiss, governance, hooks, ciVersion}) is the stable wire format for MCP clients and follow-up tooling.
The text surface prints:
- One pulse line with total events and total sentinel-miss count (
passwhen zero misses,noteotherwise). - An event-type breakdown line (one
<type>=<count>token per non-zeroEventType). - Claude Code hook health: whether the runtime has actually been observed, whether the observed engine version matches the current CLI, and the last firing time (or
never observed) for session start, prompt submit, before edit, after edit, and session stop. - A non-blocking CI warning naming each GitHub Actions workflow that invokes an unversioned or floating
npx claddingpackage. Numeric selectors such as[email protected]and[email protected]stay quiet. - Governance counts for gate runs, done attempts and rejections, stop blocks, known-failing Stop exits, blocked fingerprints reproduced by a later gate, and attestation state.
- When sentinel-miss events exist:
by phase/by cause/by fallbackaggregates from the v0.3.39 telemetry payload.- Top-5 missed sentinels (
CONVENTIONS_MD/ARCHITECTURE_YAML/SCENARIO_FLOWS/CAPABILITIES_YAML/WHY/WHAT/PURPOSE) sorted by count desc, name asc. - Last 3 unique dispatcher error strings (most recent first; errors are truncated to 200 chars at the emit site).
- A one-line tuning hint.
Exit codes
0— events.log was either missing (greenfield) or readable. A greenfield workspace prints a friendly note and exits 0; a healthy host with zero misses also exits 0 with apassline.1—events.log.jsonlexists but cannot be parsed as JSONL (corrupt telemetry).
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 · 45 lines · 93 tokens per session scan A e530159f5d3a
doctor is a skill published in the GitHub repository qwerfunch/cladding (14 stars, last pushed 4d ago), licensed MIT. It adds 93 tokens to every session and 856 once invoked, about $0.0005 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-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-explain
Deep walkthrough of code, a diff, or the whole project — problem, entities, flow, load-bearing-line rationale, side effects, assumptions, breakage. Use when learning unfamiliar code or auditing a diff.
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.