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/plannernpx skills add qwerfunch/cladding --skill plannergit 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 | $0.00053 | $0.01321 |
| Opus 5 | $0.00026 | $0.00660 |
| Sonnet 5 | $0.00011 | $0.00264 |
| Haiku 4.5 | $0.00005 | $0.00132 |
Grade A, and why
planner 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planner
The Planner is a selectable role brief (formerly librarian) — a scope plus outcome conditions and evidence obligations the host may embody with any agent shape, not an agent cladding mandates spawning. It owns the Tier A spec SSoT — spec.yaml + per-feature spec files in spec/features/ + spec/scenarios/. See docs/ssot-model.md for the full 4-tier model.
Sources (what you read, by Tier)
| Tier | Artifacts | Why you read it |
|---|---|---|
| A | spec.yaml, spec/features/<slug>-<hash6>.yaml, spec/scenarios/<slug>-<hash6>.yaml |
your write target |
| B | spec/architecture.yaml, spec/capabilities.yaml, docs/project-context.md |
cross-validate when editing A; e.g., new features[] binding in capabilities.yaml ↔ feature you just added |
You do NOT read Tier C (conventions — developer owns it) or Tier D (audit — observability owns it).
What you do
- Add new features with hash-based id
F-<hash6>(v0.3.9+): filename<slug>-<hash6>.yaml,id: F-<hash6>,slug: <slug>. LegacyF-NNNfiles stay sequential — never migrate. - Author EARS-compliant ACs (
AC-N); every feature ships at least one. - For load-bearing decisions (non-obvious ordering, invariant, trade-off a future editor could undo), record WHY in that AC's
notes(## Decision/## Why/## Trade-off); skip obvious ACs. Seedocs/ssot-model.md§ Capturing WHY. - Bind new features to existing scenarios via the scenario's
features[]array (see Scenarios policy below). - When adding user-facing features, update the matching capability's
features[]inspec/capabilities.yamlsoCAPABILITIES_FEATURE_MAPPINGstays clean. - Mark features as
archived(witharchived_at+archive_reason). - Walk
clad sync --propose-archivecandidates — STALE_SPECIFICATION emits suggestions; you confirm each before writing. - Split
spec.yamlinto per-feature spec files (spec/features/*.yaml) when the master crosses ~1k lines. - Edit
spec/architecture.yamlandspec/capabilities.yamlbetween scans — Tier B, edit-friendly; next scan diverts new body to.cladding/scan/*.proposal. - After every edit, validate with
clad syncand check withclad check --strict.
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 · 74 lines · 53 tokens per session scan A 2ca87ed1fe99
planner is a skill published in the GitHub repository qwerfunch/cladding (14 stars, last pushed 3d ago), licensed MIT. It adds 53 tokens to every session and 1,321 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.