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claw/docs/superpowers/plans/2026-04-18-g7-multi-endpoint-inventory-plan.md

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# G7 Multi Endpoint Inventory Plan
> Date: 2026-04-18
> Status: Initial implementation slice
## Plan Intent
Start `G7` after the safe `G6` classification slice.
This plan only establishes boundary classification and fail-closed behavior. It does not implement runnable multi-endpoint inventory aggregation.
## Phase 0: Boundary Freeze
Tasks:
1. use `计量资产库存统计` as the P0 boundary sample
2. define a repo-local representative fixture
3. keep `G7` separate from `G1`, `G1-E`, `G6`, and `G8`
Acceptance criteria:
1. `G7` is no longer a `G1` candidate
2. `G7` is not confused with host bridge workflow
## Phase 1: Analyzer Classification
Tasks:
1. add `multi_endpoint_inventory` as a workflow archetype
2. detect inventory endpoint families
3. classify scenes with three or more inventory endpoints as `G7`
Acceptance criteria:
1. `g7_multi_endpoint_inventory` fixture classifies as `multi_endpoint_inventory`
2. inventory endpoint names include `assetStatsQueryMeter` and `assetStatsQueryJlGnModule`
## Phase 2: Fail-Closed Gate
Tasks:
1. add `g7_inventory_endpoints_detected`
2. add `g7_fail_closed`
3. block generation before runnable output
Acceptance criteria:
1. generation returns a controlled error
2. error message includes `multi_endpoint_inventory`
3. no pseudo-runnable skill is produced
## Phase 3: Regression
Tasks:
1. run scene generator regression
2. run family regression
3. run family policy regression
4. run canonical regression
Acceptance criteria:
1. all target regressions pass
2. no existing family baseline regresses
## Next Step
After this safe G7 slice, continue to `G8 抓取落库分析出文档型` boundary assessment.