assistant-claw/skills/claw-boss-distiller/SKILL.md

name	description	version	author	license	metadata
claw-boss-distiller	Distill the boss's mental model from outgoing email corpus into a 5-layer boss_skill.md (Expression DNA / Mental Models / Decision Heuristics / Anti-Patterns / Honest Boundaries). Derived from nuwa-skill (MIT). Drafts only — boss confirms every change.	0.1.0	Moments / Atlas team (adapted from alchaincyf/nuwa-skill, MIT)	MIT	hermes category tags related_skills upstream_dependency boundaries atlas mental-model distillation nuwa boss-os atlas claw-email-parser claw-report-writer alchaincyf/nuwa-skill all_new_rules_default_to_status_draft never_apply_changes_without_explicit_boss_confirm

claw-boss-distiller

Purpose

Capture and codify how the boss thinks, decides, and writes — so the rest of Atlas's skills judge the way the boss would judge, and the Brief reads in the boss's voice.

This is the heart of the "老板 OS" / "女娲 skill" promise. Without this, Atlas is generic; with this, Atlas becomes a personal layer.

Heritage

Adapted from alchaincyf/nuwa-skill (MIT). The original distills public figures from open data; we replace the corpus with the boss's private outgoing email and add boss-confirmation gates.

We vendor the upstream references/extraction-framework.md and adapt:

• Data source: outgoing email (last 6 months by default)
• Output: boss_skill.md (5 layers, in the boss's primary writing language)
• Audit gate: every produced rule starts as status: draft and requires boss confirmation to become status: confirmed

Inputs

• Boss outgoing email corpus (from state/extracted/, filtered from = boss email)
• Current boss_skill.md (for diff)
• Optional: 3–5 sample threads where the boss made a notable decision (boss can hand-pick for first run)

Outputs

• boss_skill.md (proposed new version)
• boss_skill.diff.md (vs current)
• boss_skill.evidence/ directory (JSON per rule with source email IDs and quoted excerpts)

5-Layer Output Structure

# boss_skill.md

## Layer 1 — Expression DNA
- Tone: …
- Sentence length distribution: …
- Signature phrases: …
- Greeting / closing patterns: …
- Few-shot examples (5 representative emails)

## Layer 2 — Mental Models (3–7 frameworks the boss reaches for)
- "先抓主要矛盾" — applied when …
- "凡事预则立" — applied when …
- (etc. — each with 2–3 example threads as evidence)

## Layer 3 — Decision Heuristics (~50 if-then rules, the L1 ruleset)
- R-01: 超过 5 个工作日无回复的项目 → Stalled  [confidence: high; evidence: 7 instances]
- R-02: 客户方 2 次以上主动催办 → 升级红色风险
- … (each rule: id, condition, action, confidence, evidence count, status, last-fired)

## Layer 4 — Anti-Patterns (what the boss explicitly avoids)
- AP-01: 不接受"我以为是别人在跟"作为停滞理由
- AP-02: 不在客户面前批评内部员工
- … (each: id, rule, evidence)

## Layer 5 — Honest Boundaries (what Atlas should NOT do)
- HB-01: 不替老板回复客户邮件 (V0)
- HB-02: 不给员工打 A/B/C 评级
- HB-03: 跨客户数据隔离，不在 A 客户报告里出现 B 客户信息
- … (these come from SOUL.md + boss-confirmed extensions)

4-Stage Workflow (from nuwa)

Stage 1 — Multi-Path Collection

6 collection paths (adapted to email context):

1. Outgoing emails by intent: 催办 / 决策 / 转交 / 否决 (4 buckets)
2. Threads where boss intervened mid-conversation (high-signal moments)
3. Email replies under 50 words (压缩态思维)
4. Email replies over 200 words (完整推理)
5. Threads with customer-side complaints — how boss responds under pressure
6. Threads marking project completion — how boss closes things

Stage 2 — Triple Verification

Every candidate rule must pass:

1. Cross-domain occurrence — pattern appears across ≥ 3 different projects/contexts
2. Predictive power — given a new thread, the rule predicts the boss's action correctly
3. Exclusivity — pattern is distinctive to this boss vs generic corporate norms

Patterns failing any check become Stage-1 evidence only, not rules.

Stage 3 — Skill Construction

Assemble the 5-layer document. Draft status on every rule.

Stage 4 — Quality Validation

• Run on 10 held-out historical threads — does the rule predict boss's actual reply?
• Run on 5 currently-undecided threads — produce a recommendation, present alongside boss's eventual decision
• Compute hit rate; rules with hit rate < 70% downgraded or retired

Boss Confirmation Loop

1. Distiller produces boss_skill.md draft + diff
2. Atlas sends boss a "Quarterly Skill Review" email with the diff and a per-rule action checklist
3. Boss replies with acceptances / edits / rejections (parsed via simple structured-reply format)
4. Atlas applies confirmed changes, archives prior version under boss_skill.history/YYYY-Q*.md

Failure Modes

Failure	Behavior
Insufficient data (< 200 outgoing emails)	Halt distillation, surface to boss with explanation
Stage-2 verification yields < 10 rules	Distillation marked "preliminary", boss audit deferred
Boss does not respond to review within 30 days	Atlas sends one reminder; if still no response, freeze current boss_skill.md, log "review skipped"

Sample Distillation Run

Input: 1247 outgoing emails over past 90 days
Stage 1: 412 candidate signals across 6 paths
Stage 2: 73 pass cross-domain, 51 pass predictive, 38 pass exclusivity
Stage 3: 38 rules organized into 5 layers
Stage 4: hit rate 81% (well above 70% threshold)
Output: boss_skill.md v2 (12 new rules, 8 revised, 3 retired vs v1)
Boss action: review meeting scheduled