Borrowing it
Nothing to install: this file belongs to acartine/foolery. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/acartine/foolery/main/.claude/skills/foolery-configure/SKILL.mdgit clone --depth 1 https://github.com/acartine/fooleryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/acartine/foolery/foolery-configure)<a href="https://agentmods.dev/skills/acartine/foolery/foolery-configure"><img src="https://agentmods.dev/badge/skills/acartine/foolery/foolery-configure.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00095 | $0.01838 |
| Opus 5 | $0.00048 | $0.00919 |
| Sonnet 5 | $0.00019 | $0.00368 |
| Haiku 4.5 | $0.00010 | $0.00184 |
Grade A, and why
foolery-configure 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 8d 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/foolery-configure
Produce a valid ~/.config/foolery/settings.toml and
~/.config/foolery/registry.json by inspecting the host, asking the user at
most four questions, and validating the result against the shipped schema.
Contract
The authoritative spec for settings.toml is the foolery config CLI:
foolery config schema— prints JSON Schema (Draft 2020-12) of the file.foolery config validate [path]— exits0withOK <path>,1with a field-path breakdown on schema violation,2on file/TOML error.
Treat those two commands as the contract. Never guess field names or
defaults — read them from foolery config schema.
Inputs to load before asking anything
Run these in the shell and read their output:
cat ~/.config/foolery/settings.toml— existing settings (may not exist).cat ~/.config/foolery/registry.json— existing mounted repos (may not exist).foolery config schema— current schema.- For each of
claude,codex,opencode,gemini,copilot: runcommand -v <name>to see whether the CLI is on PATH. For each that resolves, probe for its available models (e.g.claude --help,codex --help,opencode models,gemini models,copilot --list-models). If a probe is unclear, ask the user which models they want — do not assume.
The only four questions you may ask
Ask no more than these, in this order. Skip any whose answer is already unambiguous from existing files or from a single detected CLI.
- Which agent vendors? — from the detected subset of
claude,codex,opencode,gemini,copilot. - Which models per vendor? — one or more per selected vendor, using the probed model list.
- Dispatch mode? —
basic(one agent per action) oradvanced(weighted pools per workflow step). - Which repos to mount? — absolute paths to add under
registry.json.
If a required value cannot be answered, stop and ask the user. Never pick a default to paper over a missing answer — follow the "fail loudly, never silently" rule.
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.
- 8d ago First seen · 171 lines · 95 tokens per session scan A deefd90d3c8a
foolery-configure is a skill published in the GitHub repository acartine/foolery (54 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 1,838 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.
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write-documentation
Use when writing or substantially rewriting human-facing prose: documentation, README, guides, blog posts, emails, Slack messages, PR descriptions, release notes, or any text a human will read. Not for code comments, commit messages, or agent-to-agent communication.
document-release
Use when implementation on a branch is complete and it is about to be merged or PR'd — or when finishing-a-development-branch reaches its docs-audit gate — and after code changes are committed, to ensure all project documentation accurately reflects shipped code. Covers README, ARCHITECTURE, CONTRIBUTING, CHANGELOG…
writing-plans
Use when you have a spec or requirements for a multi-step task, before touching code.
getting-up-to-speed
Orients on an unfamiliar or stale codebase at the start of a session, after compaction, or whenever the project state is unclear. Loads beads context, deep-dives the codebase, and produces a structured 'current state' summary. Triggers on phrases like "catch me up", "where are we", "orient me", "what's the state of…
stress-test
Use when a design, plan, or decision needs adversarial scrutiny before proceeding. Interrogates every branch of the decision tree, providing recommended answers and forcing explicit agreement or pushback. Triggers on "grill me", "stress test this", "poke holes", "challenge this design", or when…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.