ce9f27320a
This adds the full Atlas (总助 Claw / 老板视角项目执行雷达) scaffolding as a sibling profile to the existing Vega general-purpose assistant. All Atlas content lives under atlas/ to keep the existing top-level skeleton intact. What's included: - atlas/IDENTITY.md, SOUL.md, USER.md, AGENTS.md, MEMORY.md, BOOTSTRAP.md, HEARTBEAT.md, TOOLS.md (+ zh-CN mirrors) — full OpenClaw 8-piece set matching the zero-cca convention - atlas/skills/ — 6 sub-skills with frontmatter: claw-email-parser / claw-project-tracker / claw-people-observer / claw-customer-radar / claw-boss-distiller / claw-report-writer - atlas/skills/claw-boss-distiller/ — adapter notes for nuwa-skill, 5-layer boss_skill seed template (23 rules across Expression DNA / Mental Models / Decision Heuristics / Anti-Patterns / Honest Boundaries), and a complete synthetic distillation demo (10 input emails -> validated 5-layer output) - atlas/mcp-tools/email-extractor/ — Python implementation of stages 1-3 (fetch + decode + dequote), 7 pytest tests passing, CLI: atlas-extract - atlas/state-schemas/ — formal JSON schemas for project / person / customer cards with the no-employee-rating hard constraint baked in - atlas/client-deck/ — 2-page client-facing pitch document - autopilots/atlas-*.yaml — 5 autopilot configs (daily / weekly / monthly / quarterly + andon event-triggered) for a future Multica-side scheduler Notes: - nuwa-skill (MIT, https://github.com/alchaincyf/nuwa-skill) NOT vendored; fetch at deploy time via instructions in atlas/skills/claw-boss-distiller/upstream/README.md - Vega-side prompts/skills/tools/autopilots/docs scaffold left untouched - Top-level README.md updated with a brief Atlas pointer; rest preserved |
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claw-boss-distiller — Demo Run
A synthetic distillation, end-to-end, on a fictional 中国 SME 老板 "王总". Use this to:
- Show clients what
boss_skill.mdactually looks like before they commit - Validate the pipeline shape end-to-end before real client data arrives
- Smoke-test changes to
claw-boss-distiller(regression baseline)
Scenario
- Boss: 王总, founder + CEO of 一家约 80 人的企业服务公司 (toB SaaS), based in 上海
- Span: ~25 active projects, ~12 active customers, internal team of ~15 PMs/engineers/sales
- Email volume: ~40 incoming/day, ~20 outgoing/day
- Demo input: 10 boss-outgoing emails over a 14-day window (compressed sample; real distillation reads 6 months ≈ 2400+ emails)
- Languages: mostly 中文, occasional English term
Pipeline (matches SKILL.md and ADAPTER.md)
INPUT/wang-emails-*.txt (10 mock outgoing emails)
↓
[Bucket sort] classify each email into B1–B6
↓
[Triple verify] patterns must clear cross-domain + generative + exclusive
↓
[Synthesize 5 layers] Expression DNA / Mental Models / Decision Heuristics / Anti-Patterns / Honest Boundaries
↓
OUTPUT/boss_skill.demo.md (status: draft; awaits boss audit)
OUTPUT/run-summary.md (counts + verification trace)
Files
demo/
├── README.md # this file
├── INPUT/
│ ├── 01-催办-zhangsan-PRJ001.txt
│ ├── 02-决策-supplier-pick.txt
│ ├── 03-表扬-wang-onboarding.txt
│ ├── 04-否决-feature-request.txt
│ ├── 05-转交-li-customer-D.txt
│ ├── 06-mid-thread-intervention.txt
│ ├── 07-pressure-customer-A.txt
│ ├── 08-closing-PRJ022.txt
│ ├── 09-short-reply-FYI.txt
│ └── 10-long-reasoning-Q3-strategy.txt
└── OUTPUT/
├── boss_skill.demo.md # the produced 5-layer document
└── run-summary.md # the distillation log
How to read the demo
- Read 2–3 INPUT emails to get a feel for 王总's voice
- Read OUTPUT/boss_skill.demo.md and notice how each rule cites which input emails
- Read OUTPUT/run-summary.md to see which candidate patterns were promoted vs filtered out by triple verification
Caveats
- 10 emails is far below the real W1 corpus size. Real runs produce richer Expression DNA and more decision heuristics.
- 王总 is fictional; any resemblance to real bosses is coincidental.
- The demo deliberately includes one ambiguous case (email #4) to show how the pipeline marks
low_confidence.