business-insights-extractor
Maintainer-facing tool that ingests external source material (Telegram HTML exports, markdown articles, etc.) and distils it into the canonical startup-wisdom.md file consumed by the `doccraft-business` skill. Use whenever the user mentions extracting insights, ingesting a new channel export, refreshing startup wisdom, adding a source, processing a telegram export, re-running the reduce pass, updating the distilled rules, or anything else that produces or updates `startup-wisdom.md`. Do NOT use when the user is asking for business advice, working through requirements, setting priorities, or interviewing on target audience / milestones — that is the `business` skill's job.
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doccraft-queue-audit
Reconcile the dependency graph, pick-next queue, and backlog status across {{DOCS_DIR}}/stories/, {{DOCS_DIR}}/queue.md, and {{DOCS_DIR}}/backlog.md. Use after adding or editing a story (especially one with depends_on), after reshuffling priorities, or when the user asks "what can I work on next", "what's unblocked", "sanity-check the queue", "check my story dependencies", "fix the queue order", or "what parallel work is ready". In Agent mode (the tool can write files), apply objective mechanical fixes in the same turn and report what changed; in Ask / read-only mode, emit a proposal instead. Stop and report — never guess — on directed cycles, unknown depends_on ids, duplicate ids, or ambiguous editorial reorders.
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doccraft-story
Author or update product stories (a.k.a. planning docs, backlog items, tickets, specs) as Markdown under {{DOCS_DIR}}/stories/ with a YAML frontmatter contract (id, status, impact, urgency, depends_on, tags, openspec). Use this whenever the user is creating a story, reprioritising work, writing acceptance criteria, linking a story to OpenSpec or an ADR, or editing anything under {{DOCS_DIR}}/stories/ — even if they call it a spec, ticket, backlog row, or planning doc.
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outdoor-monitoring-analysis
Detects targets such as people, vehicles, non-motorized vehicles, and pets within target areas; supports batch image analysis, suitable for outdoor surveillance scenarios like courtyards, orchards, and farms. | 户外看护智能监测分析技能,检测目标区域内的人、车、非机动车、宠物等目标,支持批量图片分析,适用于庭院、果园、养殖场等户外区域看护场景
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