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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
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Strategy: Attack an isomorphism claim by demanding an explicit structure-preserving map and trying to break it. Targets any multi-language claim of the form 'X ≅ Y ≅ … across N mathematical languages'. Forces the claim to either earn the word 'isomorphism' or be demoted to 'analogy'. Methods: category theory (functor/natural-iso criteria), model theory, Lakatos monster-barring.
Strategy: Dialectic engine retuned for truth-seeking, not survival. A defender steelmans a claim into its MOST falsifiable form, a critic attacks to refute it, a judge classifies the exchange into BROKEN/CORROBORATED/UNFALSIFIABLE — the judge does NOT pick a winner or score persuasiveness. Methods: Irving debate (repurposed), Toulmin argumentation, Mayo severe testing.
Strategy: Run BEFORE building any validator (sandbox/simulation/benchmark). Builds a non-circularity matrix of theory-claim × validator-assumption to detect when a validator would 'confirm' a theory only because it was built on the theory's own premises. A circular validator's PASS carries zero evidential weight. Methods: Cartwright nomological machines, Winsberg sanctioning-of-simulations, tautology detection.
Strategy: Attack a beautiful unified result on the suspicion that its beauty is the bug. Distinguishes EARNED simplicity (forbids/predicts/subsumes) from DECORATIVE simplicity (re-describes/relabels/accommodates). Directly serves the Occam aesthetic by making it a falsifiable bar, not a vibe. Methods: Sober parsimony-as-evidence, MDL, Meehl risky prediction, accommodation-vs-prediction.
Campaign: Truth-seeking adversarial validation for scientific research artifacts (NOT publication defense). Core question: Where have we fooled ourselves, and is each load-bearing claim even falsifiable? Win-condition is INVERTED from survival/resilience to active refutation. Methods: Popper falsificationism, Lakatos Proofs and Refutations, Mayo severe testing, Platt strong inference.
Strategy: Attack the evidential weight of an 'independent convergence' claim. When N reasoning paths all reach the same conclusion, the confidence boost is real only if the paths were actually independent. Measures shared-prior / shared-blindspot contamination and corrects the over-counted confidence. Methods: Bayesian agreement-as-evidence, correlated-error analysis, jury theorem assumptions.
| 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 |