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 caoyuan-fire/engi-foundry-skill --skill engifoundry-docsgit clone --depth 1 https://github.com/caoyuan-fire/engi-foundry-skillWrote 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/caoyuan-fire/engi-foundry-skill/engifoundry-docs)<a href="https://agentmods.dev/skills/caoyuan-fire/engi-foundry-skill/engifoundry-docs"><img src="https://agentmods.dev/badge/skills/caoyuan-fire/engi-foundry-skill/engifoundry-docs/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/caoyuan-fire/engi-foundry-skill/engifoundry-docs"><img src="https://agentmods.dev/badge/skills/caoyuan-fire/engi-foundry-skill/engifoundry-docs.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 | $0.00042 | $0.00488 |
| Opus 5 | $0.00021 | $0.00244 |
| Sonnet 5 | $0.00008 | $0.00098 |
| Haiku 4.5 | $0.00004 | $0.00049 |
Grade A, and why
engifoundry-docs 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 9d 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EngiFoundry Docs
Scope
Use this supporting Skill only for an explicit request for a detailed document. Routine pause records and required PAK delivery summaries remain governed by Router and Deliver and do not load this Skill.
Read ./engifoundry.config.json, the project-owned workspace guide, the user's requested subject, and only the primary records and artifacts needed for that subject. Derive the audience, language, depth, file type, and destination from the request and project conventions. When unspecified, use the user's language, Markdown, and the closest matching project-owned documentation or artifact location.
Fidelity
- State project facts from current primary records and cite their paths where useful.
- Distinguish observed facts, accepted decisions, risks, open questions, and recommendations.
- Surface conflicting or missing evidence instead of resolving it by invention.
- Preserve exact code, commands, configuration, identifiers, and status terms when precision matters.
- Summarize source JSON and evidence; do not dump records, raw logs, prompts, or reasoning.
Human Format
Organize around what the intended reader needs to understand or do. Use a literal title and descriptive section headings; include a short summary only when it improves navigation. Match structure to content rather than forcing a fixed template:
- tables for comparisons, status matrices, inventories, or repeated fields;
- bullet lists for unordered facts and numbered lists for actual sequences;
- fenced code blocks for code, commands, configuration, schemas, or exact output;
- blockquotes for material warnings, constraints, or quoted source decisions;
- short paragraphs for explanation, causality, and conclusions.
Use direct, concrete wording. Explain necessary domain terms for the intended audience, keep each section internally coherent, and avoid duplicated conclusions, decorative prose, empty headings, and oversized tables. Risk statements name severity, fact, impact, and evidence. Recommendations identify their factual basis and never masquerade as completed work.
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.
- 9d ago First seen · 37 lines · 42 tokens per session scan A 0a3857bd8331
engifoundry-docs is a skill published in the GitHub repository caoyuan-fire/engi-foundry-skill (2 stars, last pushed 15d ago), licensed Apache-2.0. It adds 42 tokens to every session and 488 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 2026-08-31.
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