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).
72 lines
2.7 KiB
Markdown
72 lines
2.7 KiB
Markdown
---
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name: claw-email-parser
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description: Wraps the email-extractor MCP tool; orchestrates fetch → extract → write canonical Email JSON. The thin LLM layer that decides what to do with low-confidence extractions.
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version: 0.1.0
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author: Moments / Atlas team
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license: MIT
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metadata:
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hermes:
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category: atlas
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tags: [email, imap, extraction, atlas, intake]
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related_skills: [claw-project-tracker, claw-people-observer, claw-customer-radar]
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---
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# claw-email-parser
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## Purpose
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Atlas's intake skill. Given a date range, pull and extract emails into canonical JSON, surface anything the rule-based extractor was uncertain about, and let the LLM make a judgment call (or punt to the boss).
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## Inputs
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- `since`: ISO date — e.g. `2025-05-09` (V0 default = 12 months ago)
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- `until`: ISO date — e.g. today
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- `mode`: `full_backfill` | `incremental` (incremental reads `state/.last_sync`)
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## Outputs
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- N × `state/extracted/YYYY-MM/<thread_id>/<msg_id>.json`
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- Updated `state/.last_sync`
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- Run summary in `state/runs/YYYY-MM-DD.extract.json` with counts: fetched, extracted, failed, low_confidence_intents, new_customer_domains, new_alias_collisions
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## Judgment Rules (LLM layer)
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The MCP tool handles 95% mechanically. The LLM layer handles:
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1. **Intent classification ambiguity** (confidence < 0.6) — read the message and call it
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2. **Customer domain disambiguation** — `support@notify.clientco.com` vs `wang@clientco.com` — same customer? boss-confirm or auto-merge based on org-name presence
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3. **Alias merging proposals** — when the same human appears under 2+ identities, propose a merge with evidence (signature line match, project overlap)
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4. **Dequote escape hatch** — if regex strategies leave a clearly garbage `body_text_clean` (e.g., 90% punctuation), retry with LLM-based dequoting
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## Failure Modes
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| Failure | Behavior |
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|---------|---------|
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| Email server unreachable | Retry with backoff; if 3 retries fail, write failure to run summary, exit gracefully |
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| Single message extraction fails | Skip + log, do not abort run |
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| Quota / rate limit | Exponential backoff; checkpoint progress to resume next run |
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| LLM call fails | Mark intent = `unknown`, low_confidence = true, continue |
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## Sample I/O
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**Input:** Run incremental from `state/.last_sync` = 2026-05-08T00:00:00Z
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**Output (run summary):**
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```json
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{
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"run_id": "2026-05-09T07:30:00Z-extract",
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"fetched": 47,
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"extracted_ok": 45,
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"extraction_failed": 2,
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"low_confidence_intents": 4,
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"new_customer_domains": ["@newprospect.io"],
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"new_alias_collisions": 1,
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"duration_ms": 31200
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}
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```
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## Dependencies
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- MCP tool: `email-extractor` (see `mcp-tools/email-extractor.md`)
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- State: read `state/people/aliases.json`, `state/customers/domain_map.json`
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