bd0be97630
This repo IS Atlas (总助 Claw / 老板视角项目执行雷达). The earlier
two-profile framing (Atlas + Vega placeholder) was a misread — Vega is
the agent persona answering Multica issues, not the product. Vega has
no relationship to assistant-claw the product.
Changes:
- Move atlas/* to top-level (git mv preserves history)
- Remove empty Vega placeholders prompts/.gitkeep, tools/.gitkeep
- Delete atlas/ wrapper directory (now empty)
- Update path references in INTEGRATION-hermes.md, scripts/mirror-...sh,
docs/decisions/0001-mirror-nuwa-skill.md
- Rewrite README.md as Atlas-only, remove dual-profile language
After this commit:
- Top-level OpenClaw 8 files (IDENTITY/SOUL/USER/AGENTS/TOOLS/MEMORY/
BOOTSTRAP/HEARTBEAT + CLAUDE symlink + zh-CN mirrors)
- skills/{6 sub-skills + DESCRIPTION + README}
- mcp-tools/{spec + Python implementation}
- state-schemas/{project, person, customer + README}
- autopilots/{5 atlas-*.yaml}
- client-deck/, docs/decisions/, scripts/
The ~/.hermes/skills/atlas/ destination convention preserved (atlas as
a skill namespace on the operator's machine, distinct from source path).
64 lines
2.6 KiB
Markdown
64 lines
2.6 KiB
Markdown
# claw-boss-distiller — Demo Run
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A synthetic distillation, end-to-end, on a fictional 中国 SME 老板 "王总". Use this to:
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1. Show clients what `boss_skill.md` actually looks like before they commit
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2. Validate the pipeline shape end-to-end before real client data arrives
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3. Smoke-test changes to `claw-boss-distiller` (regression baseline)
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## Scenario
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- **Boss:** 王总, founder + CEO of 一家约 80 人的企业服务公司 (toB SaaS), based in 上海
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- **Span:** ~25 active projects, ~12 active customers, internal team of ~15 PMs/engineers/sales
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- **Email volume:** ~40 incoming/day, ~20 outgoing/day
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- **Demo input:** 10 boss-outgoing emails over a 14-day window (compressed sample; real distillation reads 6 months ≈ 2400+ emails)
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- **Languages:** mostly 中文, occasional English term
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## Pipeline (matches `SKILL.md` and `ADAPTER.md`)
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```
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INPUT/wang-emails-*.txt (10 mock outgoing emails)
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↓
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[Bucket sort] classify each email into B1–B6
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↓
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[Triple verify] patterns must clear cross-domain + generative + exclusive
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↓
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[Synthesize 5 layers] Expression DNA / Mental Models / Decision Heuristics / Anti-Patterns / Honest Boundaries
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↓
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OUTPUT/boss_skill.demo.md (status: draft; awaits boss audit)
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OUTPUT/run-summary.md (counts + verification trace)
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```
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## Files
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```
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demo/
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├── README.md # this file
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├── INPUT/
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│ ├── 01-催办-zhangsan-PRJ001.txt
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│ ├── 02-决策-supplier-pick.txt
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│ ├── 03-表扬-wang-onboarding.txt
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│ ├── 04-否决-feature-request.txt
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│ ├── 05-转交-li-customer-D.txt
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│ ├── 06-mid-thread-intervention.txt
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│ ├── 07-pressure-customer-A.txt
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│ ├── 08-closing-PRJ022.txt
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│ ├── 09-short-reply-FYI.txt
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│ └── 10-long-reasoning-Q3-strategy.txt
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└── OUTPUT/
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├── boss_skill.demo.md # the produced 5-layer document
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└── run-summary.md # the distillation log
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```
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## How to read the demo
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1. Read 2–3 INPUT emails to get a feel for 王总's voice
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2. Read OUTPUT/boss_skill.demo.md and notice how each rule cites which input emails
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3. Read OUTPUT/run-summary.md to see which candidate patterns were promoted vs filtered out by triple verification
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## Caveats
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- 10 emails is far below the real W1 corpus size. Real runs produce richer Expression DNA and more decision heuristics.
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- 王总 is fictional; any resemblance to real bosses is coincidental.
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- The demo deliberately includes one ambiguous case (email #4) to show how the pipeline marks `low_confidence`.
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