菜单
Campaign: Compile a context/ research record into an ARA (Agent-Native Research Artifact) and run a Level-2 epistemic review — no LaTeX, no narrative paper
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill ara-from-context命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | ara-from-context |
| description | Campaign: Compile a context/ research record into an ARA (Agent-Native Research Artifact) and run a Level-2 epistemic review — no LaTeX, no narrative paper |
| version | 1.0.0 |
| category | ara-from-context |
| type | campaign |
| input | A context/ directory (INDEX.md + timestamped research records + produced images) |
| output | ara/ (4-layer ARA) + ara/level2_report.json |
| tactics | ["context-review","compile-and-review"] |
| dependencies | {"tactics":["compile-and-review","context-review"],"sops":["ara-compile","ara-rigor-review","context-exploring","north-star-align"]} |
What this is: DARE 流水线最末端的"成文"环节。吃前面研究循环
(research ↔ experiment-execution 反复迭代)沉淀在 context/ 里的全部产物,
编译成一份 ARA(机器可执行的四层知识包),并做认识论审查。不写 LaTeX /
叙事论文 —— ARA 刻意反对 storytelling,要的是逻辑弧在结构上闭合。
Source of truth: 所有素材来自 context/。核心 = 末次 EE 的最终 report +
全程迭代轨迹 + 研究产出的图片。
Skill load context-review —— 回顾 context/,分三类素材,对齐大方向,
产出投喂计划。Skill load compile-and-review —— 一次 inline 跑外部 compiler 得 ../ara/,
再跑 rigor-reviewer 得 level2_report.json。运行需 ARA 的 compiler + rigor-reviewer skill 在位
(npx @ara-commons/ara-skills)。见本 repo README。
ara/(logic/ src/ trace/ evidence/ PAPER.md)+ ara/level2_report.json。
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| compile-and-review | Tactic: Compile the feeding plan into an ARA via the external compiler, then run Level-2 rigor review over it |
| context-review | Tactic: Review a context/ directory — sort material into ARA types, locate and align the north-star, and produce a feeding plan for the compiler |
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| ara-compile | SOP: Turn the feeding plan into the compiler's $ARGUMENTS and run the external ARA compiler once inline to produce ../ara/ |
| ara-rigor-review | SOP: Run the external ARA rigor-reviewer (Seal Level 2, six-dimension semantic review) over ../ara/ and pass its level2_report.json to the user |
| context-exploring | SOP: Read context/INDEX.md and sort the whole directory into three ARA material types (report line, process line, images), locate the north-star file, and draft a feeding plan for the ARA compiler |
| north-star-align | SOP: Deep-read the original north-star context, distill this ARA's overall direction, and align it with the user via the reused present-and-ask / present-candidates dialogue SOPs |