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SKILL verified Apache-2.0 Self-run

Paoding Skill

skill-longyunfeigu-paoding-skill-paoding-skill · by longyunfeigu

Use when studying, reverse-engineering, comparing, reviewing, or learning from AI skill packages, SKILL.md files, Claude/Codex skills, prompt workflows, or agent playbooks; use when the user wants reusable skill design patterns, a keep/cut review, Markdown report, structured pattern notes, or multi-page web handbook. 触发词:「庖丁」「庖丁解 skill」「解剖这个 skill」「拆解 xx skill」「这个 skill 怎么实现的」.

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Install

$ agentstack add skill-longyunfeigu-paoding-skill-paoding-skill

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

庖丁 · Skill 解剖术

Purpose

Turn a skill package into useful creator notes. Explain how the skill changes an agent's behavior, what bad output it prevents, which parts are worth copying, and which parts are too heavy for the job.

Default to the smallest useful output. A web handbook is an output mode, not the identity of this skill.

Start Here

  1. Map the source package first.
  2. Choose the output mode from the user's request:
  • Review / keep-cut advice: write a direct Markdown review.
  • Pattern extraction: write human notes and optional JSON/YAML.
  • Web handbook / 解剖手册: read references/handbook-spec.md, then

references/web-production-flow.md.

  1. Load only the companion reference needed for the current section. Examples

are calibration only; references and source files are the contract.

Workflow

1. Map the Package

Treat the input as a single SKILL.md, a skill directory, or a folder of skills.

  • Find every SKILL.md.
  • Note references/, scripts/, assets/, examples/, tests/, and metadata.
  • Read the entry SKILL.md first.
  • Read referenced files only when they explain the skill's design.
  • Inspect scripts to see which fragile jobs they take away from the agent —

and run every script that has a valid in-package input (mandatory; see 可执行工件必跑 in references/evidence-collection.md).

For a batch, analyze representative skills first, then scan the rest for repeated structures.

2. Find the Real Task Pain

Read references/pain-dimensions.md, then run its item-driven sweep:

  1. Imagine doing the task bare (a human novice, then a default agent) and

list where each would fail.

  1. Inventory every rule, script, intermediate artifact, and checkpoint in

the package. List the intermediate artifacts completely.

  1. Run each item through the three-question pain test (counterfactual,

baseline, evidence grade) and tag it with one of the seven dimension labels.

  1. Reconcile: pains the skill catches that you missed, pains you expected

that it ignores (blind spots), and residue that fits nowhere.

"这一步很难" with no observable symptom is not a finding. Difficulty claims are made against a declared baseline and carry an evidence grade.

For web handbooks, write the full ordinary-view pain scan described in references/handbook-spec.md. For shorter reviews, fold the same thinking into the findings.

When a claim needs evidence beyond the package text, or a handbook needs real artifact excerpts, follow the collection ladder in references/evidence-collection.md (mine examples/ → slice-run → targeted ablation).

The pain sweep finds what the skill defends; it systematically misses pure craft knowledge (数值表、对照表、验法、话术、命名). For web handbooks, also run the steal scan in references/steal-scan.md — six lenses, two tiers — and mark qualified candidates in place with !steal callouts.

3. Read Like a Skill Designer

Preserve three layers:

  1. How it runs: phases, gates, loops, handoffs, validation.
  2. How it is packaged: entry file, references, scripts, assets, examples,

tests, generated outputs.

  1. What design moves it contains: reusable patterns, costs, and cases where

they are too heavy.

Answer in plain language:

  • What bad AI output does this prevent?
  • What does it force the agent to do before answering?
  • What shortcuts does it block?
  • Which terms need explanation before they are useful?
  • Which moves are reusable skill patterns?
  • Which moves are platform workarounds or one-off project scars?

4. Choose the Output Shape

Review / keep-cut advice

Lead with findings. Group content as:

  • what is working;
  • what is too heavy, duplicated, or stale;
  • what to delete, merge, or move to assets/scripts;
  • what to keep as non-negotiable behavior control.

Pattern extraction

Write reusable pattern cards. Each card says:

  • bad result prevented;
  • when to use it;
  • how it works;
  • where it usually lives in the package;
  • cost and counter-case;
  • example from the source skill.

Use references/cards-patterns.md when writing many design-choice or pattern cards.

Web handbook

Use one running example through the whole handbook. Follow:

  1. references/handbook-spec.md for the content contract (六章 + 附录).
  2. references/web-production-flow.md for generation//,

handbook-brief.md, page packets, scaffold, build, and final checks.

  1. references/content-format.md when writing content/*.md — the only

hand-written layer; scripts/build-data.py turns it into data.js.

  1. references/stage-writing.md, references/cards-patterns.md,

references/source-guide-writing.md, references/visuals-and-quality.md, and references/voice-style-gate.md only for the sections that need them.

5. Quality Check

Before finishing, check:

  • Did the answer explain the behavior change, not just summarize files?
  • Can the user steal at least three concrete moves?
  • Did you preserve both workflow and package structure?
  • Did every pattern say when it is useful and when it is too heavy?
  • Did you avoid turning one project's generated output into the rule?
  • Did the source guide explain referenced files enough that the reader knows

what to read, what to skip, and what each load-bearing file controls?

  • Did an independent learner reviewer check content/source-guide.md from

a first-time reader stance, and did you record fixes/rejections in the brief?

Non-Negotiables

  • Start from the pains the skill overcomes — domain difficulties as well as

bad AI behavior. Every pain claim names an observable symptom, a baseline, and an evidence grade (references/pain-dimensions.md).

  • Keep SKILL.md lean; move detailed writing rules, templates, and visual

implementation notes to references or assets.

  • Do not rely on examples as specification.
  • Do not treat generated generation/ output as reusable skill material.
  • Collect concrete material per references/evidence-collection.md; any

synthesized artifact excerpt in a handbook is labeled 模拟样本 — the honesty rule applies to the handbook itself.

  • Use scripts/assets for repeatable mechanics instead of re-explaining them in

prose.

  • For web handbooks: data.js 是构建产物,禁止手写 — write content/*.md and

run scripts/build-data.py + scripts/check-content.py.

  • If producing a web handbook, use code-native diagrams for exact relationships

and verify referenced SVG files exist.

  • Author self-review is not enough for the voice gate. After self-checking,

dispatch an independent subagent to scan high-exposure fields — the author is blind to their own prose and self-review systematically passes AI-slop in the "summary" fields (Therefore, 为什么长这样, 最值得学的一招). See the mandatory independent-reviewer step in references/web-production-flow.md §6.

  • Source-guide self-review is also not enough. After drafting

content/source-guide.md, dispatch an independent learner reviewer to check whether a first-time reader can understand the entry logic, file cards, and private terms before opening the source. See references/source-guide-writing.md §Independent learner review.

Resources

  • references/pain-dimensions.md — the six-source dimension taxonomy, the

three-question pain test, evidence grades, and the item-driven sweep.

  • references/evidence-collection.md — the evidence collection ladder

(mine examples / slice-run / targeted ablation) and specimen rules.

  • references/steal-scan.md — the six-lens carry-away scan, two tiers,

the !steal callout, and the auto-aggregated 带走工具箱 appendix.

  • references/handbook-spec.md — content contract for multi-page handbooks

(六章 + 附录) and the ordinary-view pain scan format.

  • references/web-production-flow.md — concise web production flow: scaffold,

brief, packets, build, check, verification.

  • references/content-format.md — the content/*.md format contract shared

by the writing agent, the build script, and the renderer.

  • references/stage-writing.md — walkthrough-specific writing rules.
  • references/source-guide-writing.md — source-package reading guide rules:

package layers, referenced-file cards, reading priorities, and learning boundaries.

  • references/cards-patterns.md — difficulty-archive card rules.
  • references/visuals-and-quality.md — diagram rules and final quality checks.
  • references/voice-style-gate.md — seven hard rules plus voice gate rules.
  • references/voice-gate-examples.md — reviewer examples for common voice

failures.

  • references/web-app-visuals.md — short visual constraints for the static web

template.

  • scripts/scaffold-web-app.sh — creates the static handbook skeleton from

assets/web-app-template/ (六章 + 附录, including the 源码 page shell).

  • scripts/build-data.py — builds assets/data.js from content/*.md.
  • scripts/gen-source-data.py — mirrors the source skill's real source

(SKILL.md + references/** + scripts/**) into assets/source-data.js, which feeds the 附录 · 源码 page so readers see the actual source without leaving for the repo. Runs by default for every web handbook.

  • scripts/check-content.py — machine half of the hard gate.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.