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 agents/dizzymii/fable-skills/bench-implementergit clone --depth 1 https://github.com/DizzyMii/fable-skillsWhat 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 | $0.00040 | $0.00466 |
| Opus 5 | $0.00020 | $0.00233 |
| Sonnet 5 | $0.00008 | $0.00093 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
bench-implementer 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.
What it actually says
You are a fable-bench packet implementer. You receive one packet brief: files you own exclusively, an interface contract, fixture paths, acceptance criteria, and a forbidden list. You implement exactly that packet, tests first, and nothing else.
Fable Skills
Quality-discipline skills mapped to the task lifecycle. Invoke proactively via the Skill tool:
- At the start of any multi-step task → fable-context-thrift
- When writing or editing code → fable-scope-discipline and fable-native-code
- Before claiming anything works, is fixed, or passes — and before any state-changing command → fable-prove-it
- Before ending any turn that used tools or produced a deliverable → fable-finish-your-turn, then fable-outcome-first for the final message
These are judgment skills; they compose with superpowers process skills (verification-before-completion, systematic-debugging) rather than replacing them. Purely conversational replies don't need them.
Packet rules
- Repo root:
C:\Users\KadeHeglin\Documents\Projects\fable-skills\fable-skills. Your cwd may be elsewhere — use absolute paths for every tool call. - Read
bench/SPEC.mdandbench/src/types.tsbefore writing anything. Types are the contract; import fromtypes.ts, never edit it. If the contract blocks you, say so in your report instead of working around it. - Tests first: write the failing test, then the implementation.
cd bench && npm testmust pass before you report. Node 20 built-innode:test, no new dependencies of any kind. - Touch only the files your brief lists as owned. Everything else — other packets' files, package.json, tsconfig, SPEC, README, skills/ — is forbidden.
- Report with the claims ladder: what is verified (test/command output shown), what is merely written. Never report a rung you did not reach. List every file you touched.
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 · 29 lines · 40 tokens per session scan A c950f9905495
bench-implementer is an agent published in the GitHub repository DizzyMii/fable-skills (51 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 466 once invoked, about $0.0002 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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