Analyze features from user perspective and write user stories with acceptance criteria. Use when defining requirements, writing user stories, validating scope against project state, prioritizing features by impact, comparing approaches, analyzing user needs, or planning next work. Triggers: "user story", "acceptance criteria", "scope", "prioritize", "compare requirements", "user needs", "what to build next".
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Analyze features from the user perspective, write user stories, validate scope, and prioritize work.
Run the shared context discovery protocol in CONTEXT_DISCOVERY.md. Execute all phases in order. Store results for use in analysis below.
Parse from $ARGUMENTS:
| Mode | Description |
|---|---|
stories <feature> | Generate user stories with Given/When/Then acceptance criteria |
prioritize | MoSCoW prioritization with value/effort matrix |
scope <feature> | Feasibility and scope assessment |
validate | Cross-reference codebase against project goals |
needs | Analyze user pain points and unmet needs |
compare <A> vs <B> | Structured comparison of two approaches |
next | Recommend what to build next |
| (none) | Ask what the user needs help with |
| Mode | Produces |
|---|---|
stories <feature> | User stories (As a/I want/So that) with Given/When/Then AC, grouped by Must/Should/Could |
prioritize | MoSCoW + value/effort matrix table, ranked by impact |
scope <feature> | Assessment: User Value, Project Fit, Dependencies, Risks, Recommendation |
validate | Goals vs reality cross-reference — scope creep, missing features, readiness gaps |
needs | User Profiles, Pain Points table, Unmet Needs, Validation Questions |
compare <A> vs <B> | Dimension table (value, effort, deps, risk, fit) with clear recommendation |
next | 1-3 prioritized features from gaps, specs pipeline, and maturity analysis |
See WORKFLOW.md for detailed execution steps and output templates per mode.
Use the shared vocabulary in MATURITY_SCALE.md.
After producing the analysis, ask the user:
Save this analysis to
{output_dir}/requirements/{filename}.md?
Where {output_dir} comes from .arkhe.yaml (default: arkhe/roadmap).
| Mode | Filename Pattern |
|---|---|
stories <feature> | {feature-slug}-stories.md |
prioritize | {YYYY-MM-DD}-priorities.md |
scope <feature> | scope-{feature-slug}.md |
validate | {YYYY-MM-DD}-validation.md |
needs | {YYYY-MM-DD}-needs.md |
compare <A> vs <B> | {a-slug}-vs-{b-slug}.md |
next | {YYYY-MM-DD}-next.md |
--deep)When $ARGUMENTS contains --deep, run the full multi-agent pipeline instead of conversational analysis. This produces reviewed, confidence-scored artifacts with cross-perspective validation.
See WORKFLOW.md § Deep Pipeline for the 5-phase execution protocol.
Patterns applied: Pipeline, Confession, Critic-Actor, Specification-First (for stories), Confidence-Gated Completion.
See the PM section of LANE_DISCIPLINE.md. Stay in your lane.
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Create, review, and manage Architecture Decision Records (ADRs) with auto-numbering, template detection, quality review, and index maintenance. Use when user mentions "ADR", "architecture decision", "document this decision", "create ADR", "review ADR", editing ADR files (docs/adr/, doc/adr/, .adr/), or discussing architectural choices and tradeoffs.
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Analyze system architecture, module structure, API contracts, data models, and code patterns. Use when designing systems, reviewing module boundaries, evaluating API designs, analyzing data models, checking pattern conformance, tracing decisions, or reviewing frontend architecture. Triggers: "architecture", "module design", "API design", "data model", "boundaries", "patterns", "decisions", "frontend architecture".
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Converts natural-language descriptions or UI spec files into optimized Google Stitch prompts. Use when creating, refining, or validating design directives for Google Stitch. Use when user says "create a Stitch prompt", "optimize this for Stitch", "convert this spec to a Stitch prompt", "write a UI prompt", or mentions Google Stitch prompt authoring. Follows Stitch best practices with short, directive prompts focused on screens, structure, and visual hierarchy.
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Zero-dependency live-preview server providing an agent↔browser bidirectional companion. Watches a content directory, wraps HTML fragments in a frame template, broadcasts live-reload over WebSocket, and captures browser-side click events to a JSONL file. Use when an agent needs to show HTML to the user in a browser and react to clicks — mockups, design exploration, gallery browsing, multi-select choices, prototype iteration. Triggered by "live preview", "browser companion", "preview server", "browser mockup", "show in browser", "arkhe-preview", or any skill that wants to write HTML fragments and have the user see them reload in real time.
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Deletes merged git branches (local and remote) and flags stale unmerged branches for manual review. Use when user mentions "cleanup branches", "delete merged branches", "prune old branches", "remove stale branches", "branch cleanup", or runs /cleanup-branches command.
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Interactive Claude Code environment setup wizard. Detects existing configuration, guides through best-practice setup for Global CLAUDE.md, project scaffolding, MCP servers, hooks, custom agents, keybindings, and settings. Use when user runs /devtools:code-env-setup, mentions "setup claude code", "configure claude", "claude code setup", "environment setup", or "initialize claude code".
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