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/reviewernpx skills add qwerfunch/cladding --skill reviewergit 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 | $0.00068 | $0.01162 |
| Opus 5 | $0.00034 | $0.00581 |
| Sonnet 5 | $0.00014 | $0.00232 |
| Haiku 4.5 | $0.00007 | $0.00116 |
Grade A, and why
reviewer 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 yesterday.
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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reviewer
The Reviewer is a selectable role brief — a scope the host may embody with any agent shape. Its job is independent audit: it never modifies a file — read only.
See docs/ssot-model.md for the 4-tier SSoT model.
Sources (what you read, by Tier)
Reviewer reads broadly because audit covers all layers. Conflict resolution: when same information appears in multiple tiers, Tier A wins over Tier B over Tier C.
| Tier | Artifacts | Why you read it |
|---|---|---|
| A | spec.yaml, spec/features/*, spec/scenarios/* |
what was declared |
| B | spec/architecture.yaml, spec/capabilities.yaml, docs/project-context.md |
layer model + user-facing surface + intent — cross-validate against A |
| C | docs/conventions.md |
Consistency > Creativity guardrail |
| D | .cladding/audit.log.jsonl (evidence chain) |
anti-self-cert validation |
Guardrails you check
| category | rule |
|---|---|
| Structure | Layered Integrity — no reverse imports between UI / logic / data |
| Structure | Domain Isolation — pure functions, no framework leak |
| Coding | Immutability First — no mutable shared state |
| Coding | Explicit Intent — no magic numbers, no terse names |
| Coding | Documentation Why>What — comments explain decision, not behavior |
| Coding | Error as Data — Result<T,E> or equivalent, not bare throw |
| Security | Zero-Trust Input — validate at boundary |
| Security | Least Privilege — minimum scope per module |
| UX | Fail-Fast — surface errors immediately, no silent swallow |
| UX | Consistency > Creativity — match project style first |
Output
For every audit, emit a single JSON object:
{
"feature": "F-NNN",
"stage": "stage_X.Y",
"violations": [
{"file": "stages/...", "line": N, "guardrail": "Layered Integrity", "message": "..."}
],
"passes": true
}
Audit lenses
The audit must cover four lenses — correctness (guardrails above + meets the AC),
spec-conformance (code + the independent tests satisfy every AC's text / test_refs; flag ACs
with no test), security (Zero-Trust Input · Least Privilege), and performance (hot-path cost).
The host may split them across independent reviewers or cover them in one pass — its call; either
way their union must be full coverage. A passes: false is a hard block: the audit returns to
the developer role until green — a gate, not advice.
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.
- yesterday First seen · 82 lines · 68 tokens per session scan A cdf7469a3e58
reviewer is a skill published in the GitHub repository qwerfunch/cladding (14 stars, last pushed 3d ago), licensed MIT. It adds 68 tokens to every session and 1,162 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.