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Tactic: Review a context/ directory — sort material into ARA types, locate and align the north-star, and produce a feeding plan for the compiler
Passed 19 of 22 test cases with the skill, and 7 of 22 without it.
and 12 more in the full report
13 fixed6 passed either way2 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
Should we finalize the user alignment dialogue before locating the anchor guide document in the context directory?
| Checked | Without skill | With skill |
|---|---|---|
| The response specifies locating the north-star anchor file during context exploration prior to user alignment. | Missed | Passed |
The instructions your model reads when the skill loads.
Key question: 这批 context 里,生成 ARA 最重要的素材是什么?大方向和用户对齐了吗?
Skill load context-exploring —— 读 INDEX → 整目录分三类素材(报告线/过程线/
图片)→ 聚 arc 候选 → 定位 north-star 文件 → 草拟投喂计划。Skill load north-star-align —— 深读 north-star → 提炼大方向 → 复用
present-candidates/present-and-ask 与用户对齐 → 回填投喂计划的大方向 + arc 范围。① 对齐过的大方向 ② 完整投喂计划(主干文件 / trace 素材 / 图片清单 / arc 范围 /
大方向),交给 compile-and-review。
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| 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 |
test cases passed, vs 7 / 22 without
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