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 collindjohnson/manas --skill manas-answergit clone --depth 1 https://github.com/collindjohnson/manasWrote 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/collindjohnson/manas/manas-answer)<a href="https://agentmods.dev/skills/collindjohnson/manas/manas-answer"><img src="https://agentmods.dev/badge/skills/collindjohnson/manas/manas-answer/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/collindjohnson/manas/manas-answer"><img src="https://agentmods.dev/badge/skills/collindjohnson/manas/manas-answer.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00024 | $0.00198 |
| Opus 5.5 | $0.00010 | $0.00079 |
| Sonnet 5.5 | $0.00005 | $0.00040 |
| Haiku 4.5 | $0.00002 | $0.00020 |
Grade A, and why
manas-answer 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 today.
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
Call reasoning.answer with the question. Manas retrieves current authorized evidence, invokes the configured local generation provider, and checks its citations. Use the returned outcome, answer, citations, and knowledgeGaps together.
For insufficient_evidence, explain the evidence gap. For local_model_not_configured, report the suggested local-model setup fix; do not route the evidence to a hosted model or a shell-based generation fallback. For grounding_failed, do not present the rejected answer as supported.
Cite the returned document ID, revision, commit, and span near factual claims. If evidence conflicts, preserve the conflict instead of choosing an unsupported assertion. Generated answers are derived results and must not be captured as independent primary facts.
CLI access is manas operation reasoning.answer --input '{"question":"..."}' with the configured brain/service.
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.
- today First seen · 13 lines · 24 tokens per session scan A cffadd345165
manas-answer is a skill published in the GitHub repository collindjohnson/manas (0 stars, last pushed yesterday), licensed MIT. It adds 24 tokens to every session and 198 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 2026-10-23.
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