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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
Passed 12 of 17 test cases with the skill, and 3 of 17 without it.
and 11 more in the full report
12 fixed4 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
What is the exact JSON output file path produced by the six-dimension semantic audit after reviewing the compiled directory?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies `ara/level2_report.json` as the evaluation report artifact | Missed | Passed |
The instructions your model reads when the skill loads.
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.
test cases passed, vs 3 / 17 without
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