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 skills add griffinwork40/agent-afk --skill contractgit clone --depth 1 https://github.com/griffinwork40/agent-afkWrote 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/griffinwork40/agent-afk/contract)<a href="https://agentmods.dev/skills/griffinwork40/agent-afk/contract"><img src="https://agentmods.dev/badge/skills/griffinwork40/agent-afk/contract/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/griffinwork40/agent-afk/contract"><img src="https://agentmods.dev/badge/skills/griffinwork40/agent-afk/contract.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.00708 |
| Opus 5.5 | $0.00012 | $0.00283 |
| Sonnet 5.5 | $0.00006 | $0.00142 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
contract 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- contract — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Contract
For each sub-agent you plan to dispatch, define a schema before the call:
goal— one-sentence objectiveinputs— data/context the sub-agent receivesartifacts— named structured fields expected back (not freeform prose)non_goals— what the sub-agent must NOT dofailure_modes— how to report blocked or partial workdomain(optional) — the knowledge domain for this task. Guides how research, specification, and verification adapt. Common values:software,research,design,business— but any freeform string works (e.g.,healthcare,legal,education). When omitted, infer from context: git repo present →software; PDFs/papers/citations in working directory →research; design files/brand assets →design; financial models/strategy docs →business. Default fallback:software.
Embed the schema at the top of every sub-agent's prompt and require results in that exact shape. Instruct each sub-agent explicitly: "Return ONLY the schema fields. No preamble, no analysis prose, no explanation — begin your response with the first schema field." When sub-agents return, validate field-by-field. If any artifact is missing, malformed, or wrapped in prose, re-dispatch only the failing sub-agent with the gap cited. Merge only schema-valid responses.
Also instruct each sub-agent to stop on non-convergence: if repeated attempts at the same sub-goal stop making progress after a few tries, do not keep retrying — return the best partial result through the schema's designated failure/partial channel (failure_modes, or whatever blocked/unverified field that agent's schema defines), naming what could not be resolved. Activity is not progress.
Epistemic confidence
Recommended for all sub-agents. Add to your return schema:
confidence— low / medium / high — how confident is the sub-agent in the completeness and accuracy of its findings?coverage_gaps— what the sub-agent couldn't access, verify, or search (e.g., proprietary databases, paywalled sources, unpublished practitioner knowledge, subjective judgment areas)boundary_flag— if the sub-agent hit an epistemic boundary, name it:non-falsifiable(claim can't be tested),low-coverage(search was limited),tacit-knowledge(unwritten knowledge required),unprecedented(genuinely novel, no baseline),time-sensitive(answer depends on current state), ornonerecommended_action— what should happen next:proceed(findings solid, move ahead),human-gate(pause for human judgment before acting),re-retrieve(try different search strategy or sources),elicit(generate prompts to validate with domain experts)
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.
- 1mo ago First seen · 38 lines · 29 tokens per session scan A 0ea822d8124f
contract is a skill published in the GitHub repository griffinwork40/agent-afk (61 stars, last pushed today), licensed Apache-2.0. It adds 29 tokens to every session and 708 once invoked, about $0.0001 per session on Opus 5.5. 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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