「fea」の検索結果

Generates EditMode and PlayMode tests using NUnit, mapped from GDD Gherkin scenarios. Use when writing tests, validating features, ensuring code quality, or verifying behavior after changes. Triggers on requests like "write tests for this", "test the health system", "add unit tests", "verify this works", "add PlayMode tests", "test this feature", "write integration tests", "make sure this doesn't break", "add test coverage", "TDD this feature", or any task involving test creation, test-driven development, or quality assurance. Maps Given/When/Then scenarios directly to test methods using NUnit assertions.

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Verify that an application works correctly using `stably verify`. Use when an AI agent has made code changes and needs to validate the feature works in a real browser. The command describes expected behavior in plain English and reports a PASS/FAIL/INCONCLUSIVE verdict — no test files generated. Triggers on: "verify this works", "stably verify", "check if this works", "validate my changes", "verify my feature", "does this work", "check the app", "verify the feature".

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Guide for annotating ENCODE peaks with genomic features using ChIPseeker and GREAT. Use when users need to assign peaks to genes, determine genomic feature distribution (promoter, intron, intergenic), or perform gene ontology enrichment of peak-associated genes. Trigger on: peak annotation, ChIPseeker, GREAT, peak to gene, genomic feature, promoter enrichment, gene ontology, peak distribution, TSS distance, nearest gene.

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Audit feature specs against India's Digital Personal Data Protection (DPDP) Act. Use this skill when: - Writing or reviewing any feature that handles user data (especially children's data) - Auditing a spec's Personal Information section for completeness - Checking a feature against DPDP Act 2023 requirements - Preparing compliance documentation before engineering review - Verifying masking, retention, and consent policies are defined for all PII

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Write a Product Requirements Document (PRD). Use when the user says "write a PRD", "document this feature", "product requirements for X", "write requirements", "I need a PRD", "pitch this feature", or wants to formalize a feature or product idea into a structured doc - even if they don't explicitly say "PRD".

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Authentication & Authorisation control plane for Yuzu — the canonical entry point for any work on RBAC, OIDC SSO, SAML, SCIM, MFA/TOTP, AD/Entra integration, API tokens, session lifecycle, enrollment, and the audit/evidence chain. Use when the user says "/auth-and-authz", "/auth", "/iam", asks to plan or implement an enterprise A&A feature, asks "what's our auth gap to enterprise readiness", asks to audit current auth state against SOC 2 CC6.x / Workstream B, or starts work that touches `auth_*`, `rbac_*`, `oidc_*`, `api_token_*`, `enrollment_*`, or `cert_store.*`. The skill bundles current-state inventory, required-features inventory, gap matrix, the canonical workflow for adding a new A&A feature, and the load order for the routed reference docs.

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Turns an existing Product Requirements Prompt at .ai/[feature]/prp.md into a step-by-step task list of parent tasks and sub-tasks, saved to .ai/[feature]/tasks.md and committed. Use when a PRP is ready to be broken down into implementable work, or when planning how a feature will be built before any implementation starts. To write the PRP itself first, use prp- generation.

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Use when copy-catting, replicating, or adapting features from external systems, repos, apps, or ideas into the current project. Triggers on 'copy this from', 'replicate', 'clone this feature', 'how does X do Y', 'chom', 'like how X does it', 'port from', 'build like', '1:1 copy'. NOT for packing the current project (see mk:pack); NOT for one-shot URL-to-markdown fetches (see mk:web-to-markdown).

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Environment configuration manager for 12-factor config, feature flags, and multi-environment management. Activate on: environment variables, ConfigMap, feature flags, 12-factor config, dotenv management, config per environment, runtime config. NOT for: secret storage (use secret-management-expert), IaC provisioning (use terraform-module-builder), CI/CD variables (use github-actions-pipeline-builder).

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Extracts cfDNA fragmentomics features (DELFI genome-wide short/long ratios, WPS nucleosome positioning, Griffin GC-corrected accessibility profiles, end-motifs/MDS, OCF) for cancer detection and tissue-of-origin from plasma WGS. Centers on the nuclease-footprint reframe (every feature re-reads one nucleosome object), the mandatory GC correction, and the cross-protocol non-comparability that breaks naive classifiers. Runs FinaleToolkit (real CLI/Python, MIT) and the Griffin Snakemake pipeline; DELFI is a method, not a package. Use when deriving fragment-based signal from cfDNA, choosing a feature family for detection vs subtyping, or diagnosing why a fragmentomic model failed validation.

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Visualises RNA-modification data with transcript-feature metagene plots (Guitar GuitarPlot; MetaPlotR; deepTools computeMatrix scale-regions), peak-centred heatmaps (ComplexHeatmap; deepTools plotHeatmap), IP-vs-input paired browser tracks (log2 IP/input bigWig via deepTools bamCompare; pyGenomeTracks; Gviz; IGV/UCSC track hubs), DRACH sequence-logo plots (ggseqlogo; MEME), feature-distribution stacked bars, and volcano/MA plots for differential modification. Establishes stop-codon enrichment in the metagene plot as the biological QC anchor for any MeRIP dataset (Dominissini 2012; Meyer 2012). Use when producing the canonical metagene plot with stop-codon enrichment as a QC anchor, building paired IP/input genome-browser tracks at single-locus resolution, plotting peak-centred heatmaps clustered by condition, summarising peak distribution across transcript features, generating DRACH motif logos as sanity checks, rendering volcano plots of differential m6A, or reproducing the stop-codon enrichment plot.

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Add Wasp's built-in features to your app: auth, email, jobs, and more. These are full-stack, batteries-included features that Wasp handles for you. Use when the user wants to add meta tags, authentication (email, social auth providers), email sending, database setup, styling (tailwind, shadcn), or other Wasp-powered functionality.

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Fornece orientação para treinar e analisar Autoencodificadores Esparsos (SAEs) usando SAELens para decompor ativações de redes neurais em features interpretáveis. Use ao descobrir features interpretáveis, analisar superposição ou estudar representações monossemânticas em modelos de linguagem.

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Load this skill when building any web feature, reviewing architecture decisions, or evaluating JavaScript dependencies. Under no circumstances build features that break completely when JavaScript is unavailable or fails. Absolutely always start with semantic HTML, layer CSS enhancements, and add JavaScript as the final, optional layer. Prioritize resilience and universal access over cutting-edge features.

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[Documentation] Use to author, audit, amend, or test-spec a business Feature Spec. The single spec skill — modes draft|init|update|audit|amend create/maintain the tech-free 8-section Feature Spec; draft authors a provisional spec from an idea/requirement (no code yet, Evidence: TBD); tests generates Section 8 TC-{FEATURE}-{NNN} test specifications; sync reconciles §8 TCs ↔ executing test code. Per-mode procedure lives in references/{author,tests,sync}.md.

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[Workflow] Use when activating the Business Feature Documentation workflow for 8-section tech-free feature docs.

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[Investigation] Use when about to author a new Feature Spec from an idea — investigate all existing Feature Specs AND related code logic first to surface related/overlapping/affected specs, missing features, missing test cases/user stories, system unknowns, and the invariant landscape, before any spec is drafted.

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[Workflow] Use when activating the Big Feature workflow for large or ambiguous research-driven feature work.

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Generate a Product Requirements Document (PRD) for a new feature. Use when planning a feature, starting a new project, or when asked to create a PRD. Triggers on: create a prd, write prd for, plan this feature, requirements for, spec out.

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Acceptance-test newly added features using browser automation, happy-path flows, screenshots, UX notes, and a written report. Use when asked to test a feature, verify a recent UI change, or check whether an app workflow works.

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既存プロダクトへの機能追加の仕様を対話で固め、既存コード・既存仕様との整合を調査して REQ-# 契約付きの docs/dev/<対象>/spec.md を作成・改訂するスキル。/feature-spec <対象名> で明示的に呼び出されたときのみ使用する。

Periodic pass that keeps a project's verification skill and feature map honest: parallel source readers per feature, one live session driving every feature, at most one PR of proven corrections. Use for /maintain-verification-skill or "audit the verify skill".

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Orchestrate end-to-end backend feature development from requirements to deployment. Use when coordinating multi-phase feature delivery across teams and services.

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Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.

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。