「fea」の検索結果

Central entry point of the afonsoft agent harness. Use when starting a new project, resuming an existing one, planning features/Epics/releases, or running any multi-step agent-driven work. Validates and reconciles SPECs (SDD), audits the codebase and harness for gaps (security, architecture, performance, hygiene), proposes improvements, fragments work into GitHub Issues, delegates implementation/QA/review to specialized skills, and re-validates everything until delivery. Also use to review unapproved SPECs, reconcile open GitHub Issues with code, or run a final gap check before closing a release.

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Use when the user needs to create or refine a feature SPEC SDD before implementation.

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Detect anomalies in procurement data using Qdrant vector operations. Covers centroid-based outlier detection, near-duplicate finding via batch recommend, amount z-score analysis, and vendor variance scoring. Use when building anomaly detection, fraud detection, or data quality features.

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Semantic search over Qdrant Cloud collections using the Python client. Covers vector search, filtered search, prefetch+RRF fusion, group API, recommend API, discovery API, batch queries, scroll, and payload indexing. Use when building search features, adding new query types, or working with qdrant-client.

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Build spend analytics and dashboards from Qdrant vector data. Covers bulk scroll extraction, aggregation patterns, vendor grouping, and Chart.js visualization. Use when building analytics features, aggregating procurement data, or creating dashboards.

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Use after PROJECT_GUIDE.md exists, when the user asks if a project is worth their time, should they build vs buy, or invokes project-worth-my-time. Follow-up to explain-new-project—weighs project context (files, git history, chat) to recommend whether to invest in a repo, cherry-pick a feature, park the idea, pass, or use an existing polished product instead. Optionally enriched by a personal-memory MCP (e.g. Pieces) when one is available.

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Use when exposing app features to App Intents, Shortcuts, Siri, Spotlight, widgets, controls, or system actions — small safe AppIntents, AppShortcutsProvider, AppEnum/AppEntity, parameters, and open-vs-background behavior.

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Run before building anything new — a pre-build gate that decides whether an idea deserves its own tool, judged from both the agent lens (legible, drivable, automatable) and the human lens (will I touch it, do I want to maintain it). Trigger on "should I build X", "starting a new project / app / tool / repo", "is this worth making", "want to spin up", or any new-build intent — even if the word "checklist" never appears. Outputs a backed GATE.md with checkmarks and a one-line verdict note in the project root docs. Do NOT load for small config tweaks, one-off scripts, bug fixes on existing things, or anything that is clearly a feature of something you already run.

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Use when implementing any feature or bugfix, before writing implementation code

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Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback

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Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

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Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

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Use when completing tasks, implementing major features, or before merging to verify work meets requirements

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Use when landing a stack of dependent GitHub PRs (A ← B ← C, where each bases on the one below) onto master, merging a PR whose base is another open PR's branch, or whenever a request mentions "stacked PRs", "PR stack", "dependent PRs", or merging several related PRs in sequence. Requires every same-repository dependency chain to use GitHub's official stacked-PR feature before landing so GitHub owns stack-wide rules, CI, ordering, retargeting, and merge state.

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EMR/EHR development patterns for healthcare applications. Clinical safety, encounter workflows, prescription generation, clinical decision support integration, and accessibility-first UI for medical data entry. Use when building EMR or EHR features such as encounter workflows, prescription generation, or clinical data entry UI.

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You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

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Preview a signed-off design one release phase at a time — cut it down into a series of phase screens, each showing only what exists by that phase with the layout untouched, then put them on a scrubber you drag to watch the screen fill in release by release. Use when the user wants a Phase 1 / MVP version of an existing wireframe or mockup, phased or staged screens, a design sliced by release phase or story map, or wants to see what a screen looks like before later features land.

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Record a WebM demo video of a UI flow with shot-scraper video — a YAML storyboard drives the browser (click, type, scroll, wait) with an animated cursor overlay, so a reviewer can watch the feature instead of driving it. Use to attach motion evidence to a UI sign-off (#307), to turn an issue's "How to test" steps into a watchable clip, or when asked to "record a demo", "make a video of this flow", "show me it working".

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Track work as GitHub issues in this monorepo — create epics + child/sub-issues, label them consistently by package/app, and tie them into the commit workflow. Use when planning a feature, breaking work into tasks, or asked to "track this in GitHub", "make issues", "set up tracking".

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Data Scientist role within the AID methodology. Activate when working on: EDA, feasibility assessment, experiment planning, ML architecture, model development & validation, or production deployment & monitoring. Stack-agnostic — ask the user for their stack at the start of any new project.

日本語の概要は準備中です。原文の説明を表示しています。

AID Phase 4 - Development phase. Use for implementing features, TDD practices, code reviews, transitioning from planning to QA.

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Cucumber BDD integration for AID methodology. Gherkin-first acceptance criteria with executable specifications. Use for writing feature files, step definitions, and running acceptance tests.

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AID Phase 1 - PRD creation. Use for user stories, acceptance criteria, scoping features, transitioning from discovery to tech spec.

日本語の概要は準備中です。原文の説明を表示しています。

Build pages using ONLY existing atomic-design components. REQUIRES atomic-design skill. Use for composing pages, creating views/features from existing components.

日本語の概要は準備中です。原文の説明を表示しています。