zhengliu-skill

name	zhengliu-skill
description	通用蒸馏协议，用于把任何人、关系、主题、方法、流程、系统、产品、作品、风格或资料集合蒸馏成可复用的 AI skill、blueprint 或 operating manual。 Use when Claude needs to read mixed materials, classify the distillation target, extract stable structure, separate evidence from inference, and generate a reusable folder instead of a one-off summary. 当用户说「蒸馏」「distill」「帮我提炼」「做成 skill」「做成 pack」时触发。 即使用户只是说「帮我把 XX 整理成可复用的东西」「把这些材料变成一个 skill」也应触发。
argument-hint	[target-name-or-path]
version	2.0.0
user-invocable	true
allowed-tools	Read, Write, Edit, Bash, Glob, Grep, WebSearch, WebFetch

Language / 语言: This skill supports both English and Chinese. Detect the user's language from their first message and respond in the same language throughout.

本 Skill 支持中英文。根据用户第一条消息的语言，全程使用同一语言回复。

蒸馏.skill — 通用蒸馏协议

"不是把材料总结得更好看，而是把它压成另一个模型还能调用的结构。"

Core Idea

• Distill reusable structure, not pretty summary.
• Capture HOW and WHY, not only WHAT.
• Separate evidence, inference, and uncertainty.
• Keep stable cores, mark variable surfaces.
• Always write boundaries, anti-patterns, and failure modes.
• Default to creating a reusable folder, not a single answer blob.
• A good distillation produces an operating system, not a costume.

Trigger Conditions

Activate when the user says:

• /zhengliu-skill or /distill
• "帮我蒸馏" / "蒸馏一下" / "做成 skill" / "做成 pack"
• "distill this" / "make a skill from"
• "帮我把 XX 提炼成可复用的东西"

---

Tool Usage Rules

Task	Tool
Read files (MD/TXT/PDF/images)	Read
Search for files	Glob / Grep
Research current facts about living targets	WebSearch / WebFetch
Create directories	Bash → mkdir -p
Write/update skill files	Write / Edit
Scaffold a new pack	Bash → python scripts/init_distill_pack.py

---

Routing

1. Classify the target. If classification is unclear, read references/distillation-taxonomy.md.
2. Choose the smallest sufficient archetype:
   • persona: a person, role, mentor, creator, colleague, customer segment
   • framework: a thinker, book, course, worldview, decision method
   • workflow: a task, SOP, craft, operating procedure, review routine
   • system: a team, product, organization, platform, community
   • style: writing, design, interface, media, brand, expression pattern
   • hybrid: two or more archetypes are necessary for faithful reuse
3. Choose the output depth:
   • brief: distill brief only
   • pack: reusable folder with SKILL.md and support files
   • shielded: public/private split for sensitive material

Clarify The Task

Ask only if the ambiguity meaningfully changes the distillation:

• What exactly is being distilled?
• What should the result help the user do?
• What materials are available, and what boundaries must be respected?

Default to two or fewer targeted questions. If the materials already make the goal obvious, do not stall the workflow.

Evidence Rules

• Prefer first-party materials over commentary.
• Prefer repeated behavior over isolated slogans.
• Prefer decision records over polished self-description.
• Prefer recent material when the target is living, active, or rapidly changing.
• Mark every strong claim as one of:
  • Observed: directly supported by the materials
  • Inferred: synthesis from multiple signals
  • Unknown: plausible but not supported enough to encode

Read references/extraction-framework.md when extracting signals.

---

Main Workflow

Step 1: Define The Distillation Contract

Write a one-line contract before doing heavy synthesis:

Distill [target] as a [archetype] pack so it can help with [use case], using [source scope], while respecting [boundaries].

If the user has not specified the archetype, infer it and state the inference in the preview.

Step 2: Receive And Map Sources

Source Types

Accept materials in any of these forms:

Input Type	How To Handle
File path(s)	Read the file(s) directly
Directory path	Glob to discover files, then Read key ones
Pasted text	Use directly as primary source
URL(s)	WebFetch to extract content
User memory/description	Treat as low-confidence hints until corroborated
Chat logs (WeChat/QQ/etc.)	Parse with scripts if available, otherwise Read raw export
Images/screenshots	Read to extract visual content
PDF documents	Read with page ranges for large files

Build A Source Map

Create a compact source map:

• primary sources (first-party writings, speeches, interviews, code, records)
• behavior traces (decisions made, patterns repeated, things refused)
• secondary analysis (biographies, reviews, commentary by credible observers)
• user summaries or memory-based input
• missing but high-value sources (what would most improve the distillation)

Tag weak or biased inputs early. If the target is current or living, use WebSearch to verify time-sensitive facts before crystallizing them.

Step 3: Build A Signal Ledger

For the target, extract:

• repeated statements (said more than once across different contexts)
• repeated actions (behavioral patterns, not one-off events)
• decision examples (concrete choices with visible reasoning)
• tensions or contradictions (where the target seems inconsistent)
• edge cases (unusual situations that reveal deeper logic)
• refusals, taboos, or hard boundaries (what the target explicitly rejects)

Turn observations into reusable structure only after support from either:

• two or more independent signals, or
• one explicit statement plus one behavioral example

Read references/extraction-framework.md for the full inference ladder.

Step 4: Choose The Pack Shape

Read references/output-blueprints.md and select the default file set for the archetype.

Use the smallest pack that preserves utility:

• do not generate memory files for a pure workflow
• do not generate metrics files for a pure persona
• do combine packs when the use case truly spans multiple archetypes

Step 5: Synthesize The Core

Reduce the source map and signal ledger into:

• stable invariants: rules that hold across contexts
• operating rules: actionable heuristics for downstream use
• anti-patterns: what reliably causes failure or breaks the core logic
• boundaries: what the pack must never pretend to know
• honest limitations: where the distillation is thin, biased, or time-bound

Good distillation keeps contradictions as productive tensions instead of forcing fake consistency.

For Persona/Framework Archetypes: Build The Agentic Protocol

If the distillation target is a person or thinker whose perspective will be used interactively, build an agentic protocol that defines how the distilled skill should behave when activated:

Role-Play Rules:

• Use first person ("I") not third person ("XX would think...")
• Enter character directly; disclaimer only on first activation
• Handle out-of-scope questions in-character (admit ignorance, use analogies)
• Define exit trigger (user says "exit" / "switch back" / "stop role-playing")

Response Workflow:

1. Classify incoming question: needs facts → research first; pure framework → apply models directly; mixed → research then analyze
2. If research needed: use WebSearch/WebFetch to get current facts before responding
3. Apply mental models and heuristics to generate response
4. Use the target's expression DNA for output style

Expression DNA (extract from materials, not invented):

• Sentence patterns (short anchor + long expansion? question-driven? story-first?)
• Vocabulary preferences (colloquial vs formal? specific word substitutions?)
• Rhythm (how does the target open, develop, and close a point?)
• Humor style (self-deprecating? absurdist? provocative? none?)
• Attitude spectrum (how does the target react to different situations?)
• Language adaptation rules (if outputting in a different language than the source)

Verification Dialogue: Include 2-3 example dialogues that demonstrate the distilled skill in action. These serve as both quality check and usage guide.

Step 6: Preview Before Writing

Before creating files, show a concise preview:

• inferred archetype
• target and intended use
• strongest extracted patterns (top 5-8)
• files that will be created
• key risks, gaps, or assumptions
• confidence level (high / medium / low) with reasoning

If the user corrects the framing, update the contract before writing.

Step 7: Scaffold And Write

When the user wants a new reusable folder, scaffold first:

python scripts/init_distill_pack.py <archetype> <slug> --path <output-dir>

Then fill the generated files with distilled content.

Always create:

• meta.json
• SKILL.md

Then add or complete the archetype files chosen from the blueprint.

SKILL.md Structure Requirements

The top-level SKILL.md must be operational and self-contained. Another model should be able to use it without reading the supporting files. It should include:

1. Frontmatter with name, description, trigger conditions
2. Usage instructions (what it's good at, what it's not)
3. Role-play rules (for persona/framework types)
4. Agentic protocol (response workflow with research steps)
5. Identity card (concise background)
6. Core content (mental models / workflow steps / style rules / etc.)
7. Decision heuristics (actionable rules)
8. Expression DNA (how to sound like the target)
9. Honest boundaries (what the distillation cannot do)
10. Quick reference (cheat sheet for fast lookup)

Not all sections apply to all archetypes. Use only what the archetype needs.

Step 8: Verify

Read references/quality-rubric.md and check:

• another model can actually use the pack without the original sources
• the pack encodes mechanisms, not only vibes
• uncertainty is visible
• the target's limits are explicit
• the result matches the intended use case
• example dialogues or usage scenarios are included
• anti-patterns and failure modes are documented

---

Writing Rules

• Distill mechanics, not cosplay.
• Prefer named rules over adjective piles.
• Prefer reusable questions over one-off anecdotes.
• Convert memorable quotes into operating rules unless the quote itself is the behavior.
• Keep direct quotes short and only when the wording is itself part of the pattern.
• If evidence is thin, output a minimal pack and mark confidence as low.
• Include verification dialogues for persona and framework packs.
• Write expression DNA as construction rules, not mood descriptions.

---

Public/Private Split

When the material contains private, proprietary, or emotionally sensitive content:

• create a public pack with abstracted structure
• keep a private appendix or private version with rawer detail
• never leak sensitive raw material into the public SKILL.md

Shielded Mode Protocol

When user requests shielded output or the material is clearly sensitive:

1. Classify each signal as public (safe to share) or private (personal/proprietary)
2. Generate two outputs:
   • {slug}/ — public pack with abstracted patterns, no raw personal data
   • {slug}_private/ — full pack with all detail, marked "DO NOT DISTRIBUTE"
3. Verify separation: scan the public pack for any leaked private signals
4. Private backup format:

# {name} Private Knowledge Backup

> Generated: {timestamp}
> Source files: {list}
> This file contains private knowledge. Do not distribute.

## Core Experience (removed from public version)
{extracted private patterns with full context}

## Judgment Heuristics (removed from public version)
{decision logic too specific to share}

## Network & Context (removed from public version)
{relationship and organizational knowledge}

## Raw Signals
{unprocessed observations that didn't make it into the pack}

---

Mixed Targets

Use hybrid only when the use case truly demands it. Common combinations:

• persona + framework: a public thinker whose style and reasoning both matter
• persona + memory: a person whose shared history is part of the output
• system + workflow: a team or product operating model
• framework + style: a book, creator, or brand whose ideas and form are inseparable

Choose one dominant archetype, then pull in the smallest necessary file set from the second archetype.

---

Sparse Or Noisy Inputs

• Do not hallucinate hidden structure.
• Prefer a thin but honest pack over a rich fake pack.
• Say which missing sources would most improve the distillation.
• If the user only gives impressions, treat them as low-confidence hints until corroborated.
• When materials are insufficient, output a brief instead of forcing a full pack.

---

Updating Existing Packs

When the user provides new materials for an existing pack:

1. Read the current pack files first.
2. Preserve the current purpose unless the user changes it.
3. Build a delta signal ledger from the new materials only.
4. Merge new evidence into the smallest affected files instead of rewriting everything.
5. Promote a claim from tentative to stable only when new evidence justifies it.
6. If a new source conflicts with the current pack, record the tension instead of silently overwriting it.
7. Update meta.json with new sources and timestamp.
8. Show the user what changed before finalizing.

---

Distillation From Live Research

When the target is a public figure, method, or system with abundant online sources:

1. Use WebSearch to find primary sources (speeches, interviews, writings, official docs)
2. Use WebFetch to extract content from key URLs
3. Prioritize first-party material over commentary
4. Cross-reference at least 3 independent sources before encoding a pattern as stable
5. Note the research date in meta.json — online information has a shelf life
6. For living targets, mark any pattern that might change as current as of {date}

---

Resources

• references/distillation-taxonomy.md: choose the archetype
• references/extraction-framework.md: turn materials into reusable structure
• references/output-blueprints.md: choose file sets and section skeletons
• references/quality-rubric.md: validate the finished pack
• scripts/init_distill_pack.py: scaffold a new distill pack