assemble
免费Dev-Critic loop: implement, review, fix — repeat until clean
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Pick a Linear PBI, spec it, assemble it, then hold at the gate with a Boeing list for HITL clearance. Does NOT ship.
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安装前可以查看交给 AI 代理的指令内容。
Taxi a Linear PBI from the backlog to a fully-implemented, reviewed, but-not-yet-shipped state, then hold at the gate with chocks in place and present a Boeing list to the human for clearance.
The aircraft is fueled, checked, and ready, but does not move until ground control says so.
ONLY when invoked exactly as /prep-for-launch. This skill does not auto-trigger, does not fuzzy-match, and does not apply to "do the next thing" requests. If the user did not type /prep-for-launch, do not use this skill — compose the underlying commands manually instead.
Run the full Linear-PBI-to-pre-flight pipeline:
/next-task's logic) — or use the one in $ARGUMENTS if provided./spec's logic)./assemble's Dev→Critic loop)./ship.pnpm check / lint / test:run) without explicit HITL clearance./ship is a separate, explicitly-invoked step.If $ARGUMENTS contains a Linear PBI ID or issue number, use it directly.
Otherwise, follow the /next-task workflow:
Backlog-state issues for the ASDLC team via Linear MCP.Output: the selected PBI, its acceptance criteria, and a one-line justification for the pick.
Invoke the /spec workflow against the selected PBI:
specs/{feature-domain}/spec.md, read it and update only where the PBI introduces new requirements.specs/content-articles/spec.md conventions.Output: the spec path and a delta summary (new sections, changed sections, untouched sections).
Invoke the /assemble Dev→Critic loop against the PBI + spec:
/dev sub-agent./critic sub-agent.Output: number of cycles, final verdict, and the consolidated list of all findings raised across cycles (resolved and unresolved).
Do NOT run pnpm check / smoke tests yet. Do NOT commit. Do NOT push. Compile the Boeing List and present it to the human.
## Boeing List — <PBI ID>: <title>
### Aircraft
- **PBI:** <Linear issue link>
- **Spec:** <spec path>
- **Branch:** <current branch>
- **Cycles:** <N dev-critic cycles>
- **Final verdict:** <PASS | PASS WITH NOTES>
### Q/A Findings
(from critic cycles — both resolved and unresolved)
- [resolved] <finding> — fixed in cycle <N>
- [unresolved] <finding> — <reason it was left>
- [note] <verdict-level note from final critic pass>
### Dev Findings
(from the dev sub-agent's own work — discoveries, assumptions, deviations)
- <assumption made about ambiguous requirement>
- <decision to deviate from spec, with rationale>
- <new constraint discovered that should be crystallized back to spec>
- <files modified, beyond the obvious>
### Held for HITL Clearance
(things the human must decide before clearance)
- [ ] Approve all Q/A findings as acceptable
- [ ] Approve all dev assumptions / deviations
- [ ] Confirm spec updates (if any) reflect intent
- [ ] Authorize smoke tests (`pnpm check`, `pnpm lint`, `pnpm test:run`)
- [ ] Authorize push to remote
### Recommended Next Steps (after clearance)
1. Run smoke tests locally
2. If green, invoke `/ship` to commit and push
3. If red, return to `/assemble` with the new findings
After printing the Boeing List, stop. Do not proceed further. Wait for the user to clear individual items or instruct the next move.
Inherits from /assemble:
/prep-for-launch. No auto-triggering, no helpful inference.$ARGUMENTS
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Dev-Critic loop: implement, review, fix — repeat until clean
中文简介正在准备中。当前显示原文说明。
Assess source material against the ASDLC Knowledge Base and produce an evidence-calibrated Content Review Report.
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Perform an adversarial review of the current uncommitted changeset, validating it against project contracts and architectural intent.
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Triage the content corpus against the latest GSC snapshot and produce a prioritized refresh report. Read-only: reports, never edits.
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Implement features, fix bugs, and keep the codebase healthy and maintainable. Works from a defined PBI, issue, or task description.
中文简介正在准备中。当前显示原文说明。
GEO+SEO audit of asdlc.io — analyzes the codebase for Generative Engine Optimization across AI citability, technical infrastructure, content quality, schema markup, and knowledge base discoverability. Produces a composite GEO Score (0-100) with prioritized action plan.
中文简介正在准备中。当前显示原文说明。