Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-enginenpx agentmods add skills/yogsoth-ai/de-anthropocentric-research-engine/ara-compileWrote 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/yogsoth-ai/de-anthropocentric-research-engine/ara-compile)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/ara-compile"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/ara-compile/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/yogsoth-ai/de-anthropocentric-research-engine/ara-compile"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/ara-compile.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 21 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00033 | $0.00667 |
| Opus 5.5 | $0.00013 | $0.00267 |
| Sonnet 5.5 | $0.00007 | $0.00133 |
| Haiku 4.5 | $0.00003 | $0.00067 |
Grade A, and why
ara-compile 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 2mo 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
SOP: ARA Compile
Key question: 怎么把投喂计划喂给外部 compiler,一次抽出一份内部一致的 ARA?
Preflight
先确认外部 compiler skill 可 load(ARA skills 已装:npx @ara-commons/ara-skills)。
若不可用,提示用户安装并停下,不要静默继续。
Why one inline call, not multi-subagent
ARA 的 cross-layer binding(claim→proof→evidence、tree→claim)必须全局一致。
分批 compile 会各自从 C01 起撞 ID、断 tree,汇总等于重缝半成品 —— 正是 ARA 要消灭
的事。compiler 自带覆盖度循环(max 3 轮)+ 内建 Task 工具;真需要并行由它内部
自理,本 SOP 不越俎拆分。
Procedure
-
把投喂计划整理成 compiler 的
$ARGUMENTS:- 主干文件清单 + trace 素材清单 + 图片清单的路径(compiler 按路径读);
- 标注哪些是主干(报告线 → claims/problem);
- 大方向作为约束文本(约束 PAPER.md 的 title/abstract);
--output ../ara/(与context/平级,天然不会被下次 review 当 context 吃回去)。
例:
compiler context/2026-06-06-01-30-stage7-...md context/2026-06-05-...stage6...md \ context/figures/*.png \ --output ../ara/ \ 主干=stage7(报告线);其余为过程线/图片;大方向:<从 north-star-align 来的一段> -
一次 inline 运行:
Skillload compiler,传上面的$ARGUMENTS。 compiler 跑 4 阶段(语义解构 → 认知映射 → src 层 → 探索图抽取)+ 覆盖度循环- Seal Level 1。
-
Seal Level 1 不过:compiler 自带 fix-iterate(2–3 轮),本 SOP 不接管; 若仍不过,把失败报告透传给用户,停。
Output
<workspace>/ara/(logic/ src/ trace/ evidence/ PAPER.md),Level 1 已过。
交给 ara-rigor-review。
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.
- 2mo ago First seen · 58 lines · 33 tokens per session scan A 76794b2e13a8
ara-compile is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (510 stars, last pushed 14d ago), licensed Apache-2.0. It adds 33 tokens to every session and 667 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 2026-09-03.
ara-compile compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ara-compileyogsoth-ai/de-anthropocentric-research-engine | Skill | 510 | 14d ago | Apache-2.0 | A | 33 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |