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Skill Content Fit Check

@ aquarius-wing1862026.7.10skill-content-fit

Decide whether a document, prompt, or experience is complete enough to turn into a reusable skill, and list what is missing if it is not.

FeaturedAI Engineering

Basic info

Name
Skill Content Fit Check
Description
Always trigger for: 创建新 Codex skill 前的准入判断、把尚未成型的项目知识/经验教训/执行规则/误差反馈/事故复盘/文档片段转成 skill 前的内容适配评估、判断内容是否值得沉淀成可复用能力。 Also trigger for casual phrasing: "这个适合写成 skill 吗", "能不能固化成 skill", "要不要沉淀成能力", "这段经验值得做成规则吗", even if the user does not use the word skill. Do NOT trigger when: 输入已经是 skill、SKILL.md、已安装 skill,或用户是在审查、优化、更新、修复现有 skill。

Skill Content Fit Check

Judge whether a piece of raw material qualifies as a reusable skill — verdict is pass / reject, and on reject the skill only lists what's missing rather than inventing a fake workflow.

When to use it

Postmortem crystallization:

I just wrapped a production postmortem and I have the corrective pattern in hand — I want the skill to judge whether this is a reusable process or a one-off fact before I decide whether to crystallize it.

Lesson-learned reuse:

The project hit a snag, I've written up a summary — I want a plain answer on whether it qualifies as a skill. If yes, route it downstream; if no, tell me exactly what's missing.

Doc snippet upgrade:

A chunk of project docs / AGENTS.md / an issue discussion feels like it could be crystallized into a capability, but I'm not sure — I'd rather run the acceptance check first than jump straight into writing.

Screen several ideas:

I have a pile of incident notes / feedback / lesson fragments and I want the skill to filter which ones deserve crystallization, so the rest can just be archived.

Not for:

Content is already a skill / SKILL.md / installed skill → skill-improve-workflow; naming a skill's slug (lowercase, hyphenated) → skill-domain-framing; paired display names → skill-name-generation; writing SKILL.md after a pass verdict → skill-create-workflow.

What it produces

On reject, never fabricates a fake workflow — only lists what's missing. That's the most counterintuitive part.

  • Verdict: two states only — pass (all six acceptance checks met) / reject (any hard condition missing)
  • Six-axis judgement: repeatability / trigger / executable flow / verification / boundary & counter-example — each must have at least one piece of evidence extractable from the input
  • Reject comes with a missing-fields list: what's absent from the input plus what the user needs to supply, so the next round can pass in one go
  • Pass comes with crystallization notes: draft points on trigger / workflow / counter-example / acceptance criteria for the downstream skill author
  • Will never: invent a workflow to force a reject into a pass, nor decide what to do with disqualified content (keep, archive, delete — that's your call)

Prerequisites & boundaries

Prerequisites:

A piece of content to paste in — postmortem, lesson summary, doc snippet, or feedback log. Too-short input or pure background material gets rejected on sight.

Adjacent skills:

Task Route to
Write SKILL.md scaffold after a pass verdict skill-create-workflow
Name a skill's slug (lowercase, hyphenated) skill-domain-framing
Paired English + Chinese display names skill-name-generation
Generate README after a pass verdict skill-readme-generation
Content is already a skill, review / refine it skill-improve-workflow

Out of scope:

  • Input is already a skill / SKILL.md / installed skill content
  • Just a snippet of code / a command with a "make it a skill" wrapper — no trigger scene, no boundary
  • Rewriting disqualified content into something acceptable (that's the skill author's job)

Subtle edges:

  • High-risk scenes (legal / finance / compliance / production release) relax the repeatability count, but flow and verification stay mandatory
  • One-off facts / single-user preferences / emotional feedback → always rejected, no soft-pass "check again later"

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