formated-results
Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced…
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
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill ara-from-context --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/ara-from-contextContext preview
The summary Claude sees to decide when to auto-load this skill.
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
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。
1. `Skill` load **context-review** —— 回顾 `context/`,分三类素材,对齐大方向, 产出投喂计划。 2. `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`。
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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 |
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The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced…
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