agent-device-lab
Prepare and check trusted macOS hosts for physical Android and iPhone tests with agent-device, ADB, and Xcode, or set up iPhone…
Build local semantic review slices by combining clawpatch feature maps, deepsec threat candidates, visual review maps, and optional gitcrawl/discrawl evidence for repos such as openclaw/openclaw.
$ npx -y skills add vincentkoc/dotskills --skill semantic-slicing --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/semantic-slicingContext preview
The summary Claude sees to decide when to auto-load this skill.
Build local semantic review slices by combining clawpatch feature maps, deepsec threat candidates, visual review maps, and optional gitcrawl/discrawl evidence for repos such as openclaw/openclaw.
name: semantic-slicing description: Build local semantic review slices by combining clawpatch feature maps, deepsec threat candidates, visual review maps, and optional gitcrawl/discrawl evidence for repos such as openclaw/openclaw. license: MIT metadata: source: "https://github.com/vincentkoc/dotskills"
Turn a large repo into reviewable semantic slices with evidence. Use code shape, threat candidates, issue clusters, and support chatter together so review budget lands on the right parts of the system.
Default stance: map locally first, rank second, spend agent/security-review budget last.
1. Reuse suitable tool state. Create task-owned temporary storage only when a tool requires files. 2. Read target repo instructions before scanning. For OpenClaw, read root `AGENTS.md`; subtree guides matter when reviewing a slice. 3. Verify tool setup:
4. Run deterministic maps before AI review:
5. Run `scripts/semantic-map.mjs` to merge the evidence into JSON on stdout.
6. When a visual board is requested, review it in product order:
7. Choose a cost size before running AI stages:
8. Run AI only at the chosen size:
9. Report retained paths, run IDs, counts, cost size, exclusions, and skipped expensive stages in chat. Remove only task-owned disposable scratch when no longer needed or in use. Preserve named deliverables and recovery evidence.
stateDiagram-v2
[*] --> ReadScopeAndInstructions
ReadScopeAndInstructions --> ReuseToolState
ReuseToolState --> CreateTemporaryState: required by selected tool
ReuseToolState --> DeterministicMaps: existing state sufficient
CreateTemporaryState --> DeterministicMaps
DeterministicMaps --> MergeEvidence
MergeEvidence --> ReviewBoard: visual board requested
MergeEvidence --> ChooseCostSize: inspect stdout map
ReviewBoard --> ChooseCostSize
state ChooseCostSize <<choice>>
ChooseCostSize --> ReportResults: low, no AI processing
ChooseCostSize --> TargetedAIReview: medium, explicit files and bounded controls
ChooseCostSize --> BroadAIReview: high, explicit budget and time decision
ChooseCostSize --> ReportBlocked: required budget or tool unavailable
TargetedAIReview --> ReportResults
BroadAIReview --> ReportResults
ReportResults --> [*]
ReportBlocked --> [*]We are moving from "prompt as text" to skill as runtime module. Each skill acts like a lightweight, containerized application for AI work: a stable interface, opinionated workflow, and bundled resources that can be installed, versioned, tested, and reused
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