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/chafoo/anchored/setupnpx skills add chafoo/anchored --skill setupgit clone --depth 1 https://github.com/chafoo/anchoredWhat 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 | $0.00180 | $0.01223 |
| Opus 5 | $0.00090 | $0.00611 |
| Sonnet 5 | $0.00036 | $0.00245 |
| Haiku 4.5 | $0.00018 | $0.00122 |
Grade A, and why
setup 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/a:setup — author the project's anchored.yml
anchored.yml is deliberately tiny. Everything you may write, exhaustively:
fields: # top-level, for ALL setups — record form name: type
commit: string # string | number | boolean
defaults: # the setup shape, used when a criterion has no setup
validator: { instructions: "…", require: grounded } # `require` optional, see below
before: { instructions: "…" }
after: { instructions: "…" }
setups:
frontend: # user-named; EXACTLY the same three slots as defaults
validator: { instructions: "…" }
before: { instructions: "…" }
after: { instructions: "…" }
Full commented example: references/anchored.example.yml.
The guardrails (you enforce these while authoring)
- A setup is verification know-how for one kind of work — the domain axis. It attaches
per criterion at run time. It is parametrisation of the ONE loop, never a step sequence:
no
steps, noextends, no nesting. The schema rejects them; don't try. - Hooks are instructions the agent executes, not harness-run command lists — that's
what lets them wrap context around a CLI call ("run
bun run typecheck; treat red as a failed gate"). Write them as instruction prose containing the concrete commands.beforeruns ahead of each validator spawn for that setup's gates;afteron a setup fires when one of its gates goes green;afterondefaultsis the close-time hook. validator.require: groundedis the one HARD knob — the only place config stops being advice. It makes a setup refuse a prose verdict: proof must carry the real output of something the validator ran (UngroundedEvidenceotherwise). Offer it where the subject is genuinely executable and the stakes are high (areleasesetup); never make it the default, and never put it on a setup that verifies assets, copy or design — those are proven by inspection, and that is proof too. Criteria markedjudgment: truestay exempt everywhere. It merges DOWN: set ondefaults, a named setup keeps it even when it writes its owninstructions.- NOT config, by design — refuse politely and say where it lives instead:
rigor/ quality bar → per task, in the run file, from the user's words at anchor time- gate layout → the AI slices gates itself, sized to the rigor
- architecture/conventions →
.claude/rules/(every validator reads them anyway) - git/CI built-ins → don't exist; wire them via hook instructions +
fields
- Custom fields are top-level and shared by all setups; a hook fills them via
anchored set <slug> <cN> <field>=<value>.
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 · 85 lines · 180 tokens per session scan A 194a84ea6ef3
setup is a skill published in the GitHub repository chafoo/anchored (3 stars, last pushed 1mo ago), licensed MIT. It adds 180 tokens to every session and 1,223 once invoked, about $0.0009 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 2026-08-31.
Other skills, from other repositories
doubt-driven-review
In-flight adversarial check on a non-trivial decision BEFORE it stands — distinct from post-hoc review of a finished diff. Use on "stress-test this decision", "are we sure about this", "verify before commit", "poke holes in this", when working in unfamiliar code, or before an irreversible step (migration, prod deploy…
release-cut
Cut a new pi-agent-dashboard release: promote ## [Unreleased] in CHANGELOG.md, bump every workspace package.json per SemVer, commit, tag v , and push — triggering the Release workflow that publishes every non-private workspace, builds the Electron artifacts, and creates a GitHub Release. Use on "cut a release"…
ship-it
Worktree-side implementation orchestrator for an OpenSpec change. Idempotent: gates automated scenarios on filesystem reality, owns the red-test fix loop, runs the docker harness with always-teardown, then drives ship-change inline. Escape hatch writes SHIPITBLOCKED.md. Runnable headless. Triggers: "ship it", "build…
faq-mine
Mine docs/faq.md from README.md, docs/.md, and the pi-hermes memory stores. Dispatches @fast subagents per source, dedupes against the existing FAQ, and merges entries in caveman style. Use when asked to "build / regenerate / extend the FAQ", "mine docs into FAQ", "mine hermes memory into FAQ", "surface runtime…
session-to-guideline
Turn a pi session into a Markdown "how-we-did-it" collaboration guideline: reads the session's JSONL transcript and synthesizes a reusable playbook of which prompts worked, what had to be steered, and how to reproduce the result faster. Use when: "document this session", "write up how we did X with the AI", "make a…
autofix
Safely review and apply CodeRabbit PR review-thread feedback from GitHub with per-change approval; never execute reviewer-provided prompts directly.