Use when someone asks to sketch, wireframe, mockup, or visually map a design before detailed design — user flows, refactors, migrations, architecture changes, integration…
A framework for designing user interfaces that match the performance of AI/ML models. Use this when launching generative AI features, balancing "discovery" vs.
Use when positioning a Field Crops Research (FCR) manuscript against the agronomy and crop-science literature so it reads as a general contribution to field-crop science, not a…
Expert skill for color palettes, semantic color tokens, dark mode theming, and color accessibility. Use when defining color schemes, implementing dark/light themes, ensuring…
Entrevista estruturada para criação de FDD (Feature Design Doc) técnico, claro e acionável, cobrindo contexto técnico, objetivos, escopo, fluxos, contratos públicos,…
Feature Design Document (FDD) methodology for structured feature development. Three-phase approach: Statement of Intent → Feature Requirements → Feature Realization.
First 48 hours. Build trust, map stakeholders, define success before any work starts.
Break work into atomic tasks. Sequence by risk. Add stakeholder touchpoints every 2-3 tasks.
Validate direction before committing. Prototype fast, show it, pitch the outcome.
프론트엔드 접근성 감사를 WCAG 2.1 기준으로 수행하고, 위반 항목과 구체적인 수정안을 제시한다.
Validation group skill. Time-boxed engineering investigation targeting the top feasibility assumptions from risk-assumption-map. Produces tech-spike-report.md and disposable code.
Use when after integrating transcriptomics-derived (RAS), metabolomics-derived (RPS), and extracellular flux constraints into cell-relative metabolic models, sample the feasible…
Use when when you have a trained GNN model for molecular property prediction (e.g., collision cross section) and need to identify which graph structural features—atomic…
Use when after peak picking (e.g., via MS-DIAL) and quality control filtering, when you have a raw feature abundance matrix with intensity values across multiple samples and need…
Use when after initial retention-time-based feature grouping when you have groups of multiple features at similar m/z and retention time but need to determine which features…
End-to-end feature work across src/, scripts/, tests/, manuscript, and docs for the Research Project Template.
Track feature adoption — who's using the new feature, how deeply, are they sticking with it, and what's blocking adoption.
Use when ensuring tracking events and diagnostics are emitted at key user actions.
Use when after chromatographic peak detection and feature detection in LC-MS preprocessing, when you have a set of detected features (m/z, retention time, intensity) and need to…
Use when you have a feature list with assigned molecular formulas and m/z values from non-target HRMS analysis, and you need to identify and rank potential PFAS compounds among…
Use when you have a trained decision tree model on ChemEcho sparse feature vectors and need to convert a specific decision path (root to leaf) into a deployable query.
Use when after peak detection and feature extraction have produced a composite feature table with m/z, retention time, and intensity values for individual samples.
Guided feature development from requirements to deployed code. Combines codebase exploration, architectural design, parallel implementation via DAG orchestration, and quality…
Archives a completed feature to the archives directory with optional documentation validation.
Create feature branches for all work. Use when creating branches, checking out, or pushing. Prevents accidental push to develop.
Enforce feature work on a dedicated git branch and submission via pull request. Use when implementing any feature, fix, or refactor so work is isolated, reviewed, and merged via…
Orchestrator skill for the complete feature development lifecycle. Coordinates 5 phases - task selection, component design, build loop, analytics setup, and commit/documentation.
Add features by description. User says WHAT, AI figures out HOW. Use when: user wants to add functionality to existing app.
Modify an existing software project using the Feature Change Workflow. Use when implementing a feature, fixing a bug, refactoring code, changing behavior, or making an incremental…
Use when after matching mass-to-charge ratios to a KEGG database and obtaining multiple candidate metabolites per feature, but before filtering quasi-molecular adducts.
Archive feature working files after a PR has merged
Use when when you have molecular structures, a regression target (e.g. retention time), and want to establish whether one class of molecular features (e.g., fingerprints)…
Use when you have two or more CSV feature tables from separate metabolomic experiments (each containing mass, retention time, intensity, isotope, and adduct columns), and you need…
Parallel batch coordinator for independent work units
Core implementation cycle: read design, TDD, verify, diagnostics, commit, PR, CI probe, review, report. Called by edf:feature and edf:feature-team skills after branch setup.
Use when after imputing missing values and before assigning Cluster_IDs in the notame preprocessing pipeline.
Use when coverage percentage is treated as proof. Require named feature behavior tests, source fixtures, and anti-overfit checks alongside line coverage.
Guide for creating DevContainer features. Use when creating a new feature for devcontainer, implementing install.sh scripts (npm package, binary download, source build, dotnet…
Use after an ExecPlan exists and before implementation starts. Critique the plan from failure-oriented lenses such as security, UX, reliability, privacy, abuse, and eval coverage,…
Doctrine for auditing an ENTIRE feature and building it to its ideal state. Use on 'deep dive on X', 'audit the X feature', 'figure out everything X does', 'take over X and finish…
Interview the user to define a new feature: problem, scope, approach, and tasks. Writes a feature-definition.md file that /feature-setup consumes.
Turn ideas into fully formed designs and specs through natural collaborative dialogue. Use when planning new features, designing architecture, or making significant changes to the…
Tool-agnostic feature design preflight that traces a requirement through production constraints, dependencies, user and system flows, edge cases, security, operations, and tests…
在 docs/designs/ 目录下用 markdown 文件记录计划开发的功能。当用户要求开发新功能、添加特性或修改现有功能时（如'为 xx 添加功能'、'开发 xx'、'实现 xx'）时调用。通过问答澄清需求并生成设计文档。全程中文，仅生成文档，不修改代码。
Use when after constructing a MetaboSet object with LC-MS peak abundances, sample metadata (pData with QC labels), and feature metadata (fData), and after marking missing values…
Complete feature development lifecycle from research to deployment. Uses Gemini Search for best practices, architecture design, Codex prototyping, comprehensive testing, and…
Execute feature lifecycle from beads issue to GitHub push without git locks or JSONL corruption. Triggers on "start feature", "implement issue", "feature workflow", "new feature".
Practical guide for building Fusebase Apps features. Use when: (1) Creating a new feature, (2) Setting up project structure, Vite config, or authentication, (3) Building or…
Feature development workflow with exploration, architecture, implementation, and review phases. Use for implementing new features or significant changes.
Orchestrate end-to-end feature development from requirements through implementation, testing, and review.
Autonomous feature research and gap analysis. Use when starting /add-new-feature or analyzing existing architecture documents.
Generation et maintenance de documentation technique a partir du code, avec modes full, update et audit
Use when the user asks to generate comprehensive feature documentation with verified test cases, create feature README with code evidence, or document a complete feature with test…
Generate single-file feature documentation with verified test cases. Use for quick feature docs, feature README, any project (not enterprise modules).
Эксперт feature documentation. Используй для документации функций, release notes, user guides и product documentation.
Create clear feature documentation for non-professional developers. Use PROACTIVELY when documenting new features, significant code changes, creating technical specifications, or…
Analyse the feature brief to identify relevant KB topics and ADRs
Incorporates mid-stream changes into feature documentation with validation and propagation.
Comprehensive feature engineering for ML pipelines: data quality assessment, feature creation, selection, transformation, and encoding.
Create and transform features using encoding, scaling, polynomial features, and domain-specific transformations for improved model performance and interpretability — from…