/ara-from-context
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.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/ara-from-context
Context 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
SKILL.md
ara-from-context.SKILL.mdname: 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
Campaign: ARA From Context
**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。
Flow
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`。
External dependency
运行需 ARA 的 `compiler` + `rigor-reviewer` skill 在位 (`npx @ara-commons/ara-skills`)。见本 repo README。
Output
`ara/`(`logic/ src/ trace/ evidence/ PAPER.md`)+ `ara/level2_report.json`。
<!-- BEGIN available-tables (generated) -->
Available Tactics
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 |
Available SOPs
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 |
<!-- END available-tables (generated) -->
Read more
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
Campaign: ARA From Context
**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。
Flow
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`。
External dependency
运行需 ARA 的 `compiler` + `rigor-reviewer` skill 在位 (`npx @ara-commons/ara-skills`)。见本 repo README。
Output
`ara/`(`logic/ src/ trace/ evidence/ PAPER.md`)+ `ara/level2_report.json`。
<!-- BEGIN available-tables (generated) -->
Available Tactics
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 |
Available SOPs
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 |
<!-- END available-tables (generated) -->
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
Other skills on de-anthropocentric-research-engine.
- /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 block in your reply. Do not execute the research.
Open skill - /formated-specs
Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply. Replaces the generic spec-writing step.
Open skill - /injection-fidelity
Loss-1 judge (codex role). Given one sample's de-identified dialogue and its PolicyCard, decide axis-by-axis whether the user-simulator enacted the card's per-axis pressure. Judge enactment of the card, never whether the research is good.
Open skill - /ladder-quality-order
Loss-2 judge (codex role). Over one topic's 6 shuffled research-design samples, pairwise-rank by quality using the D1–D5 standard. Emit the pairwise log; the harness computes the order and the ladder verdicts. Judge quality difference, never against academic standards.
Open skill - /optimization-loop
The optimizer brain for the ladder-foundry pretraining loop. Runs the two-level nested batch loop, delegates gating to gate_eval, attributes a failing batch to one weight (attribute-first), and recovers from disk after compaction. Control flow is fully scripted; only the
Open skill - /acu-nugget-recall
Tactic: Extract atomic units from one paper and score how much of a caller-supplied summary covers. Use for ACU-style binary or Nugget-style ternary recall checks; cannot run without a target summary.
Open skill

