「fea」の検索結果

Phased workflow for delivering a Drupal feature or non-trivial change: plan, implement, review, test, finalize. Use when building a new custom module, adding a route/form/plugin, changing entity structure or schema, or any task touching more than a couple of files. Do NOT use for typo fixes, CSS tweaks, or single-line changes — use the tiny-fix skill instead. Each phase has an exit condition; do not move to the next phase until it is met.

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VitePress documentation workflow for Software Metrics Machine docs under docs/vitepress. Use when creating, updating, reviewing, or restyling SMM documentation pages, especially feature docs that must keep CLI terminal examples and dashboard views/screenshots in sync. Covers Markdown style, VitePress tabs, command examples, dashboard screenshots, sidebar links, and docs validation. USE FOR: docs/vitepress, VitePress docs, documentation style, CLI docs, dashboard docs, screenshots, feature pages. DO NOT USE FOR: application code changes unless needed to verify documented behavior.

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Runs the full implement-and-commit loop over a task list — selects the next incomplete sub-task, implements it, runs linters and tests, marks it done, commits, and repeats until the list is finished. Use when asked to work through a feature's task list at .ai/[feature]/tasks.md unattended, or to keep going until every sub-task is complete. For a single sub-task with no commit, use task-implementation; to stop for approval between each one, use iterative-development.

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Prepare and publish upstream issues, feature requests, discussions, pull or merge requests, and patch submissions in the channel the canonical project expects. Use when reporting a problem upstream, requesting a feature, contributing a change, or asking to submit upstream.

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Generate a Product Requirements Prompt (PRP) from a feature description. Use when starting work on a new feature.

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16-phase feature orchestration workflow. Runs in the main thread as Kernel Mode. Coordinates the Lead→Developer→Reviewer→TestLead→Tester assembly line.

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三方框架特性落地（原 framework-feature-enablement ＋ framework-extension-dev 合并）： 一个入口信号「框架侧特性没落地」，内部分两分支——**分支 A 框架已有 → 使能与验证** （计数契约 + 三层证据 + 使能异常回修）；**分支 B 框架缺失 → 补齐开发** （注入点 + 代码组织/注册机制 + 合入姿势：平台注册优先 / 上游 PR / fork 钉版 / monkey 备选）。 分支 A 触发词：量化/稀疏/缓存开关没生效、融合算子没命中、使能异常或精度不符、 "起 vllm 服务""模型在框架里跑不通""把 mindiesd 接到其他框架"。 分支 B 触发词：框架没 comm-stream 掩盖、框架没缓存消费者、框架不支持某 collective/mask、 feature_* NotImplemented、要给框架补一条结构性能力。 near-miss：纯安装/权重 → env-install；纯采集/分析 → profiling-collect / profiling-analyze； 纯选档（该不该开量化、开哪一档）→ dit-perf-opt； mindiesd 仓内 pattern / 算子 / 图下发开发 → dev-workflow + pattern-dev / operator-dev / aclgraph-dev。 由 model-auto-optimization 的 S1（融合接入）/S4（有损使能）/S5（训练感知）与 §0 缺口补齐策略路由， 亦由 dev-workflow 的框架接入/验证场景指引加载。

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Choose what kind of knowledge to transfer between teacher and student models: response, feature, or relational, and decide among offline, online, self, or cross-modal distillation schemes. Best for distillation strategy selection, capacity-gap diagnosis, and transfer planning. Activate on "knowledge distillation", "teacher-student", "soft labels", "feature distillation", "online distillation", or "cross-modal transfer". NOT for generic compression checklists or unrelated training work.

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Application architecture patterns and code organization — clean architecture, hexagonal architecture, feature-based structure, dependency inversion, module boundaries, SOLID principles at module scale. Activate on "clean architecture", "hexagonal architecture", "feature-based structure", "dependency inversion", "module boundaries", "architecture pattern", "folder structure", "fat controller", "circular dependency", "IoC container". NOT for microservice decomposition (use microservices-patterns) or database schema design (use database-design-patterns).

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Auto-invoked 7-phase workflow for complex-feature intent. Includes fasttrack mode for pre-approved specs. NOT for explicit user-invoked single tasks (see mk:cook); NOT for green-field autonomous builds (see mk:autobuild); NOT for simple bug fixes (see mk:fix).

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Orchestrates single-task implementation pipeline: plan → test → build → review. Shipping is an explicit follow-up. Use for feature work, plan execution, or fixes scoped to a single task. NOT for green-field product builds (see mk:autobuild); NOT for auto-invoked workflow orchestration (see mk:workflow-orchestrator).

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Use when transforming existing code into agent-consumable surfaces — CLI (npm-publishable), MCP server (stdio/SSE/Streamable HTTP), and a companion skill. Triggers on 'agentize', 'henshin', 'expose as MCP', 'wrap as CLI', 'publish to npm', 'make LLM-accessible', 'turn into agent tool', 'expose feature as tool'. Runs when the user has existing code and wants to ship it to agents. NOT for building new code from scratch (see mk:bootstrap); NOT for reviewing or verifying existing code (see mk:review).

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Use when implementing features or writing code. TDD enforcement is opt-in via --tdd / MEOWKIT_TDD=1. Provides code patterns, skill loading, and coding standards.

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Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when creating components, pages, features, fetching data, styling, routing, or working with frontend code.

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DraftForge test infrastructure for writing backend unit tests, Playwright E2E tests, and managing test data population. This skill should be used when writing new tests, adding test fixtures, creating populate functions for new features, adding Playwright E2E specs, using login/auth fixtures, creating test users/orgs/leagues/tournaments, or understanding the test data architecture. Covers backend Django tests via Docker, Playwright config (projects, workers, sharding), test auth endpoints that expose backend login to frontend, and feature-isolated test data patterns.

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Install and configure PostHog analytics SDK in React Native applications, including event tracking, feature flags, user identification, and error tracking. Use when the user needs to add PostHog analytics, session recording, or feature flags to a React Native app.

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Fallback for general coding work that does not match any specific sextant sub-skill. Use for lightweight tasks: config changes, style fixes, utility functions, one-off scripts, or tasks too small to warrant a dedicated workflow. All dedicated sub-skills take priority over this one — check these first: sextant:fix-bug (broken behavior), sextant:debug (unknown bug location), sextant:add-feature (new functionality), sextant:modify-feature (changing existing behavior), sextant:review-code (evaluating code), sextant:write-tests (test coverage), sextant:refine-requirements (ambiguous scope), sextant:plan (multi-step sequencing), sextant:ship (release prep), sextant:migrate (cross-module upgrade), sextant:security (vulnerability audit). Only use this skill when none of the above match.

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Imports gene expression count matrices from featureCounts, HTSeq, STAR ReadsPerGene, Salmon/kallisto via tximport or tximeta, RSEM, 10X Genomics MTX/H5, AnnData H5AD, and RDS. Handles silent-miscounting traps (featureCounts -p v2.0.2 API break, STAR strandedness column choice, salmon NumReads-sum without tximport, RSEM non-integer expected_count, GENCODE _PAR_Y suffix, zero-length-transcript TPM divide-by-zero), and encodes the tximport countsFromAbundance decision tree with the "lengthScaledTPM is not TPM" warning. Use when assembling a gene-by-sample count matrix from aligner or quantifier output, importing salmon/kallisto for DESeq2 vs limma-voom, choosing strandedness column for STAR, debugging zero-count panics, or building tx2gene mapping.

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Annotate CLIP-seq peaks or crosslink sites to RNA features (5'UTR, CDS, 3'UTR, intron, splice junction, snoRNA, tRNA, ncRNA, repeat elements) with ChIPseeker, RCAS, RBP-Maps (Yeo splicing regulatory maps), and bedtools, applying feature-priority hierarchies, transcript-context resolution, and metagene aggregation. Use when characterizing where in transcripts an RBP binds, comparing peak distribution across regions, generating splicing-regulatory maps relative to alternative-splicing events, or distinguishing exonic vs intronic vs UTR binding.

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Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPseeker (R), HOMER annotatePeaks.pl (CLI), pyranges (Python), GREAT/rGREAT (regulatory domain gene-set enrichment), ChIP-Enrich (locus-length-adjusted), ENCODE SCREEN cCRE classification (PLS/pELS/dELS/CA-CTCF/CA-H3K4me3), and ENCODE-rE2G for cell-type-specific enhancer-gene linking. Handles nearest-TSS vs host-gene ambiguity, promoter window definition, and feature priority. Use when assigning genomic context to peaks, linking enhancer peaks to target genes, classifying peaks against ENCODE cCRE registry, or running gene-set enrichment on peak-associated genes.

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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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This skill recommends educating patients and families about the clinical features of remission in Cushing's syndrome when a patient achieves biochemical remission after treatment. Use when a CS patient has postoperative normal cortisol levels, reports symptom improvement, and requires guidance on long-term expectations and monitoring for recurrence.

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Decompose an MVP vision into a sprint manifest — a prioritized feature list where every feature carries explicit done-criteria (a done-record reference, named edge tests, and a wiring test). Produces the sprint manifest that `sprint-oracle` checks for completeness. Use when planning a sprint of parallel work (Slice A of the sprint-mode epic). Not a workflow phase; the manifest it writes is the completeness contract a sprint is held to.

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The sprint completeness oracle — a mechanical, exit-code-driven check that every feature in a sprint manifest is provably complete across three dimensions (a done-record reference, resolvable edge tests, and a resolvable wiring test). Fails loud with a per-feature gap list naming the missing dimension. Read-only. Use to gate a sprint before it is called done (Slice A of the sprint-mode epic), or any time you want a completeness reading.

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。