# Skill Resolver Overview

Compact view of skills by domain and tier to help routers and humans find the right skill quickly.

## ai-agent-systems

- **[core]** `ai-agent-systems/agent-evaluation` — agent-evaluation: >   Evaluate LLM agents and tool-using workflows—task success, tool accuracy,   latency/cost, safety, and regression suites. Use when shi...
- **[core]** `ai-agent-systems/agent-tool-contracts` — agent-tool-contracts: >   Design agent tools and CLI surfaces—schemas, naming, errors, idempotency, and   discoverability for LLM callers. Use when defining to...
- **[core]** `ai-agent-systems/context-window-management` — context-window-management: >   Manage LLM context budgets—prioritization, summarization, compaction, and   what to load vs reference. Use for long sessions, large r...
- **[core]** `ai-agent-systems/dispatching-parallel-agents` — dispatching-parallel-agents: >   Split independent work across parallel agents with explicit boundaries and a   parent integration review. Use only when user allows s...
- **[core]** `ai-agent-systems/mcp-builder` — mcp-builder: >   Design and implement MCP servers—tools, resources, prompts, schemas, and error   contracts for agent clients. Use when adding MCP int...
- **[core]** `ai-agent-systems/mcp-ecosystem-optimizer` — mcp-ecosystem-optimizer: Review and optimize MCP server setup—inventory, registry hygiene, config, versioning, and observability. Use when managing multiple MCP s...
- **[core]** `ai-agent-systems/rag-systems` — rag-systems: >   Design retrieval-augmented generation pipelines—chunking, embeddings, retrieval,   reranking, grounding, and evaluation. Use when bui...
- **[core]** `ai-agent-systems/subagent-driven-development` — subagent-driven-development: >   Execute an approved plan via one subagent per task with spec and quality checks.   Use only when user allows subagents and a written ...

## analysis-stats

- **[community]** `analysis-stats/shap` — shap: Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning mod...
- **[community]** `analysis-stats/statistical-analysis` — statistical-analysis: Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumptio...
- **[community]** `analysis-stats/statsmodels` — statsmodels: Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics...

## architecture

- **[community]** `architecture/system-mapping` — system-mapping: Map systems with diagrams—components, data flows, feedback loops, and causal relationships. Use for architecture understanding or stakeho...

## core-workflow

- **[core]** `core-workflow/api-and-interface-design` — api-and-interface-design: Design API and module boundaries with clear contracts, error semantics, pagination, and additive compatibility. Use before implementing R...
- **[core]** `core-workflow/architecture-decision-records` — architecture-decision-records: >   Create and maintain Architecture Decision Records (ADRs) for significant technical   choices—frameworks, data stores, API shapes, ML ...
- **[core]** `core-workflow/clarify-underspecified` — clarify-underspecified: >   Ask the minimum clarifying questions before implementing when scope, constraints,   or success criteria are unclear. Use when a reque...
- **[core]** `core-workflow/code-simplification` — code-simplification: Simplify working code while preserving behavior—remove dead paths, flatten nesting, clarify names, reduce duplication. Use after features...
- **[core]** `core-workflow/deprecation-and-migration` — deprecation-and-migration: >   Plan deprecation and migration—replacement first, consumer migration, strangler   and adapter patterns, zombie code removal. Use when...
- **[core]** `core-workflow/design-smell-review` — design-smell-review: >   Lightweight design smell review for modules and APIs—coupling, cohesion,   naming, boundaries, and unnecessary complexity. Use before...
- **[core]** `core-workflow/doubt-driven-review` — doubt-driven-review: >   Adversarial fresh-context review for non-trivial decisions before they stand.   Use for production-impacting logic, security-sensitiv...
- **[core]** `core-workflow/github-comment-triage` — github-comment-triage: >   Triage and address GitHub PR review comments systematically—classify, respond,   fix or defer with rationale. Use when a PR has revie...
- **[core]** `core-workflow/idea-refine` — idea-refine: Shape early ideas through divergent exploration and convergent narrowing before specs or builds. Use when brainstorming product features,...
- **[core]** `core-workflow/incremental-implementation` — incremental-implementation: >   Implement multi-file changes in thin vertical slices—implement, test, verify,   commit. Use when a feature touches more than one file...
- **[core]** `core-workflow/interview-me` — interview-me: Extract user intent through structured one-question-at-a-time interviews before specs or implementation. Use when requirements are fuzzy,...
- **[core]** `core-workflow/planning-and-task-breakdown` — planning-and-task-breakdown: >   Decompose specs into small, ordered tasks with acceptance criteria and verification   steps. Use when you have requirements and need ...
- **[core]** `core-workflow/receiving-code-review` — receiving-code-review: >   Receive code review feedback constructively—verify claims, prioritize fixes,   push back with evidence when needed. Use when acting o...
- **[core]** `core-workflow/requesting-code-review` — requesting-code-review: >   Request a focused code review with scope, diff context, and severity-ordered   findings. Use before merge or between plan tasks when ...
- **[core]** `core-workflow/source-driven-development` — source-driven-development: >   Ground framework and library decisions in official documentation—detect versions,   fetch relevant docs, cite sources, flag unverifie...
- **[core]** `core-workflow/spec-driven-development` — spec-driven-development: >   Write a structured spec before significant implementation—objective, commands,   boundaries, testing, and success criteria. Use when ...
- **[core]** `core-workflow/systematic-debugging` — systematic-debugging: >   Four-phase root-cause debugging—reproduce, compare patterns, hypothesize, fix with   tests. Use when errors are unclear, fixes failed...
- **[core]** `core-workflow/test-failure-triage` — test-failure-triage: >   Systematically triage failing tests by grouping errors, fixing root causes in   priority order, and verifying incrementally. Use when...
- **[core]** `core-workflow/test-first-development` — test-first-development: >   Apply test-first discipline for behavior changes and bugfixes: define expected   behavior, add or run a failing test, then implement ...
- **[core]** `core-workflow/verify-before-done` — verify-before-done: >   Require fresh verification evidence before claiming tests pass, builds succeed,   or work is complete. Use when finishing a task, cre...
- **[core]** `core-workflow/work-access-handoff` — work-access-handoff: Explain and document work access layers—repo permissions, local vs cloud environments, handoff packages for collaborators. Triggers: "han...

## data-compute

- **[community]** `data-compute/dask` — dask: Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or ...
- **[community]** `data-compute/networkx` — networkx: Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph...
- **[community]** `data-compute/polars` — polars: Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation...

## eda-research

- **[community]** `eda-research/exploratory-data-analysis` — exploratory-data-analysis: Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzi...
- **[community]** `eda-research/hypothesis-generation` — hypothesis-generation: Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable h...
- **[community]** `eda-research/umap-learn` — umap-learn: UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/p...

## frontend-engineering

- **[community]** `frontend-engineering/browser-testing-with-devtools` — browser-testing-with-devtools: Verify web apps with browser DevTools—DOM, console, network, performance, and accessibility at runtime. Use with Chrome DevTools MCP or h...
- **[community]** `frontend-engineering/frontend-ui-accessibility` — frontend-ui-accessibility: >   Build accessible UI—semantic HTML, keyboard support, ARIA when needed, WCAG-oriented   checks. Use when implementing or reviewing web...
- **[community]** `frontend-engineering/frontend-ui-engineering` — frontend-ui-engineering: Build and refine web UI—component structure, responsive layout, design tokens, state, and accessibility. Use for feature UI work beyond W...

## gstack

- **[imported]** `gstack` — gstack: Fast headless browser for QA testing and site dogfooding. Navigate pages,   interact with elements, verify state, diff before/after, take...
- **[imported]** `gstack/browser-qa/benchmark` — benchmark: Performance regression detection using the browse daemon. Establishes   baselines for page load times, Core Web Vitals, and resource size...
- **[imported]** `gstack/browser-qa/benchmark-models` — benchmark-models: Cross-model benchmark for gstack skills. Runs the same prompt through   Claude, GPT (via Codex CLI), and Gemini side-by-side — compares l...
- **[imported]** `gstack/browser-qa/browse` — browse: Fast headless browser for QA testing and site dogfooding. Navigate any   URL, interact with elements, verify page state, diff before/afte...
- **[imported]** `gstack/browser-qa/canary` — canary: Post-deploy canary monitoring. Watches the live app for console errors,   performance regressions, and page failures using the browse dae...
- **[imported]** `gstack/browser-qa/qa` — qa: Systematically QA test a web application and fix bugs found. Runs QA   testing, then iteratively fixes bugs in source code, committing ea...
- **[imported]** `gstack/browser-qa/qa-only` — qa-only: Report-only QA testing. Systematically tests a web application and produces   a structured report with health score, screenshots, and rep...
- **[imported]** `gstack/code-quality/codex` — codex: OpenAI Codex CLI wrapper — three modes. Code review: independent diff   review via codex review with pass/fail gate. Challenge: adversari...
- **[imported]** `gstack/code-quality/health` — health: Code quality dashboard. Wraps existing project tools (type checker,   linter, test runner, dead code detector, shell linter), computes a ...
- **[imported]** `gstack/code-quality/investigate` — investigate: Systematic debugging with root cause investigation. Four phases: investigate,   analyze, hypothesize, implement. Iron Law: no fixes witho...
- **[imported]** `gstack/code-quality/review` — review: Pre-landing PR review. Analyzes diff against the base branch for SQL   safety, LLM trust boundary violations, conditional side effects, a...
- **[imported]** `gstack/context-memory/context-restore` — context-restore: Restore working context saved earlier by /context-save. Loads the most   recent saved state (across all branches by default) so you can p...
- **[imported]** `gstack/context-memory/context-save` — context-save: Save working context. Captures git state, decisions made, and remaining   work so any future session can pick up without losing a beat. U...
- **[imported]** `gstack/context-memory/learn` — learn: Manage project learnings. Review, search, prune, and export what gstack   has learned across sessions. Use when asked to "what have we le...
- **[imported]** `gstack/context-memory/setup-gbrain` — setup-gbrain: Set up gbrain for this coding agent: install the CLI, initialize a local   PGLite or Supabase brain, register MCP, capture per-remote tru...
- **[imported]** `gstack/context-memory/sync-gbrain` — sync-gbrain: Keep gbrain current with this repo''s code and refresh agent search   guidance in CLAUDE.md. Wraps the gstack-gbrain-sync orchestrator wi...
- **[imported]** `gstack/deploy-ship/document-release` — document-release: Post-ship documentation update. Reads all project docs, cross-references   the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md t...
- **[imported]** `gstack/deploy-ship/land-and-deploy` — land-and-deploy: Land and deploy workflow. Merges the PR, waits for CI and deploy, verifies   production health via canary checks. Takes over after /ship ...
- **[imported]** `gstack/deploy-ship/landing-report` — landing-report: Read-only queue dashboard for workspace-aware ship. Shows which VERSION   slots are currently claimed by open PRs, which sibling Conducto...
- **[imported]** `gstack/deploy-ship/setup-deploy` — setup-deploy: Configure deployment settings for /land-and-deploy. Detects your deploy   platform (Fly.io, Render, Vercel, Netlify, Heroku, GitHub Actio...
- **[imported]** `gstack/deploy-ship/ship` — ship: Ship workflow: detect + merge base branch, run tests, review diff, bump   VERSION, update CHANGELOG, commit, push, create PR. Use when as...
- **[imported]** `gstack/design/design-consultation` — design-consultation: Design consultation: understands your product, researches the landscape,   proposes a complete design system (aesthetic, typography, colo...
- **[imported]** `gstack/design/design-html` — design-html: Design finalization: generates production-quality Pretext-native HTML/CSS.   Works with approved mockups from /design-shotgun, CEO plans ...
- **[imported]** `gstack/design/design-review` — design-review: Designer''s eye QA: finds visual inconsistency, spacing issues, hierarchy   problems, AI slop patterns, and slow interactions — then fixe...
- **[imported]** `gstack/design/design-shotgun` — design-shotgun: Design shotgun: generate multiple AI design variants, open a comparison   board, collect structured feedback, and iterate. Standalone des...
- **[imported]** `gstack/plan-review/autoplan` — autoplan: Auto-review pipeline — reads the full CEO, design, eng, and DX review   skills from disk and runs them sequentially with auto-decisions u...
- **[imported]** `gstack/plan-review/devex-review` — devex-review: Live developer experience audit. Uses the browse tool to actually TEST   the developer experience: navigates docs, tries the getting star...
- **[imported]** `gstack/plan-review/plan-ceo-review` — plan-ceo-review: CEO/founder-mode plan review. Rethink the problem, find the 10-star   product, challenge premises, expand scope when it creates a better ...
- **[imported]** `gstack/plan-review/plan-design-review` — plan-design-review: Designer's eye plan review — interactive, like CEO and Eng review. Rates   each design dimension 0-10, explains what would make it a 10, ...
- **[imported]** `gstack/plan-review/plan-devex-review` — plan-devex-review: Interactive developer experience plan review. Explores developer personas,   benchmarks against competitors, designs magical moments, and...
- **[imported]** `gstack/plan-review/plan-eng-review` — plan-eng-review: Eng manager-mode plan review. Lock in the execution plan — architecture,   data flow, diagrams, edge cases, test coverage, performance. W...
- **[imported]** `gstack/plan-review/plan-tune` — plan-tune: Self-tuning question sensitivity + developer psychographic for gstack   (v1: observational). Review which AskUserQuestion prompts fire ac...
- **[imported]** `gstack/remote-agents/openclaw/gstack-openclaw-ceo-review` — gstack-openclaw-ceo-review: Use when asked to review a plan, challenge a proposal, run a CEO review,   poke holes in an approach, think bigger about scope, or decide...
- **[imported]** `gstack/remote-agents/openclaw/gstack-openclaw-investigate` — gstack-openclaw-investigate: Use when asked to debug, fix a bug, investigate an error, or do root   cause analysis, and when users report errors, stack traces, unexpe...
- **[imported]** `gstack/remote-agents/openclaw/gstack-openclaw-office-hours` — gstack-openclaw-office-hours: Use when asked to brainstorm, evaluate whether an idea is worth building,   run office hours, or think through a new product idea or desi...
- **[imported]** `gstack/remote-agents/openclaw/gstack-openclaw-retro` — gstack-openclaw-retro: Weekly engineering retrospective. Analyzes commit history, work patterns,   and code quality metrics with persistent history and trend tr...
- **[imported]** `gstack/remote-agents/pair-agent` — pair-agent: Pair a remote AI agent with your browser. One command generates a setup   key and prints instructions the other agent can follow to conne...
- **[imported]** `gstack/scrape/browser-skills/hackernews-frontpage` — hackernews-frontpage: Scrape the Hacker News front page (titles, points, comment counts).
- **[imported]** `gstack/scrape/scrape` — scrape: Pull data from a web page. First call on a new intent prototypes the   flow via $B primitives and returns JSON. Subsequent calls on a mat...
- **[imported]** `gstack/scrape/skillify` — skillify: Codify the most recent successful /scrape flow into a permanent browser-skill   on disk. Future /scrape calls with the same intent run th...
- **[imported]** `gstack/security-safety/careful` — careful: Safety guardrails for destructive commands. Warns before rm -rf, DROP   TABLE, force-push, git reset --hard, kubectl delete, and similar ...
- **[imported]** `gstack/security-safety/cso` — cso: Chief Security Officer mode. Infrastructure-first security audit: secrets   archaeology, dependency supply chain, CI/CD pipeline security...
- **[imported]** `gstack/security-safety/freeze` — freeze: Restrict file edits to a specific directory for the session. Blocks Edit   and Write outside the allowed path. Use when debugging to prev...
- **[imported]** `gstack/security-safety/guard` — guard: Full safety mode: destructive command warnings + directory-scoped edits.   Combines /careful (warns before rm -rf, DROP TABLE, force-push...
- **[imported]** `gstack/security-safety/unfreeze` — unfreeze: Clear the freeze boundary set by /freeze, allowing edits to all directories   again. Use when you want to widen edit scope without ending...
- **[imported]** `gstack/utility/gstack-upgrade` — gstack-upgrade: Upgrade gstack to the latest version. Detects global vs vendored install,   runs the upgrade, and shows what''s new. Use when asked to "u...
- **[imported]** `gstack/utility/office-hours` — office-hours: YC Office Hours — two modes. Startup mode: six forcing questions that   expose demand reality, status quo, desperate specificity, narrowe...
- **[imported]** `gstack/utility/open-gstack-browser` — open-gstack-browser: Launch GStack Browser — AI-controlled Chromium with the sidebar extension   baked in. Opens a visible browser window where you can watch ...
- **[imported]** `gstack/utility/retro` — retro: Weekly engineering retrospective. Analyzes commit history, work patterns,   and code quality metrics with persistent history and trend tr...
- **[imported]** `gstack/utility/setup-browser-cookies` — setup-browser-cookies: Import cookies from your real Chromium browser into the headless browse   session. Opens an interactive picker UI where you select which ...

## marketing

- **[community]** `marketing/meta-ads-analyzer` — meta-ads-analyzer: Analyze Meta (Facebook/Instagram) ad performance—campaign structure, breakdowns, marginal vs average CPA, and scaling decisions. Analytic...

## meta-tools

- **[community]** `meta-tools/autoskill` — autoskill: Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and dr...
- **[community]** `meta-tools/reflect-yourself` — reflect-yourself: Self-learning system that captures corrections, discovers workflow patterns, and syncs learnings to skills and rules. Use when ending a s...
- **[community]** `meta-tools/reflect-yourself/skill-examples/phase-kickoff` — phase-kickoff: Convert the current phase doc into an ordered execution plan and propose work packages (spec-first + tiered tests), including RTL/Hebrew ...
- **[community]** `meta-tools/writing-skills` — writing-skills: >   Author and pressure-test agent skills—triggers, thin SKILL.md, references, validation.   Use when creating or revising skills in this...

## ml-dl

- **[community]** `ml-dl/pytorch-lightning` — pytorch-lightning: Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement...
- **[community]** `ml-dl/scikit-learn` — scikit-learn: Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learni...
- **[community]** `ml-dl/scikit-survival` — scikit-survival: Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with ...
- **[community]** `ml-dl/transformers` — transformers: This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or mu...

## mobile

- **[community]** `mobile/app-store-submission-packager` — app-store-submission-packager: Prepare iOS App Store and Google Play submissions—metadata, assets, compliance checks, and release checklist. Use before store upload or ...
- **[community]** `mobile/ios-testflight-github-actions` — ios-testflight-github-actions: Set up iOS TestFlight delivery via GitHub Actions—build, sign, upload—with secret hygiene and no auto-push. Triggers: "TestFlight", "iOS ...

## performance

- **[community]** `performance/performance-optimization` — performance-optimization: >   Measure, identify bottlenecks, fix, verify, and guard performance regressions.   Use for web vitals, slow APIs, heavy notebooks/pipel...

## product-growth

- **[community]** `product-growth/product-analytics-experiments` — product-analytics-experiments: >   Product analytics and experimentation—event design, funnel metrics, tracking   plans, and A/B test setup with statistical and operati...
- **[community]** `product-growth/product-offer-design` — product-offer-design: Package workflows and capabilities into clear product offers—audience, outcome, scope, and delivery format. Neutral framing without fixed...

## reflect-yourself

- **[community]** `reflect-yourself` — reflect-yourself: Self-learning system that captures corrections, discovers workflow patterns, and syncs learnings to skills and rules. Use when ending a s...
- **[community]** `reflect-yourself/skill-examples/phase-kickoff` — phase-kickoff: Convert the current phase doc into an ordered execution plan and propose work packages (spec-first + tiered tests), including RTL/Hebrew ...

## reliability-ops

- **[core]** `reliability-ops/ci-cd-quality-gates` — ci-cd-quality-gates: >   Design lightweight CI quality gates—lint, test tiers, security scans, and merge   policies. Use when setting up or improving pipeline...
- **[core]** `reliability-ops/cross-platform-error-handling` — cross-platform-error-handling: Design consistent error handling across web, mobile, and React Native—central handlers, user-facing copy, retry, and logging. Triggers: "...
- **[core]** `reliability-ops/dynamic-config-management` — dynamic-config-management: Manage application configuration—schemas, validation, .env.example, placeholder detection, fail-fast startup. Use when adding env vars or...
- **[core]** `reliability-ops/observability-slo` — observability-slo: >   Lightweight observability and SLO practice—SLIs, SLO targets, error budgets,   logs, metrics, traces, and alerting for apps and data ...
- **[core]** `reliability-ops/postmortem-writing` — postmortem-writing: >   Write blameless incident postmortems—timeline, impact, root cause, contributing   factors, and actionable follow-ups. Use after outag...
- **[core]** `reliability-ops/serverless-debugging` — serverless-debugging: Debug serverless and edge functions—limited logs, cold starts, timeouts, env/config mismatches. Use for Lambda, Cloud Functions, Workers,...
- **[core]** `reliability-ops/shipping-launch-checklist` — shipping-launch-checklist: >   Pre-launch and rollout checklist—feature flags, thresholds, rollback, monitoring,   and comms. Use before production releases or risk...

## security-appsec

- **[core]** `security-appsec/api-security-testing` — api-security-testing: >   Security testing checklist for HTTP APIs—authn/z, input validation, rate limits,   sensitive data exposure, and common OWASP API issu...
- **[core]** `security-appsec/secure-api-design` — secure-api-design: >   Design and implement secure APIs—authentication patterns, authorization models,   input validation, secrets handling, and safe defaul...
- **[core]** `security-appsec/skill-supply-chain-audit` — skill-supply-chain-audit: >   Audit third-party agent skills before install—metadata, triggers, scripts,   network/exfil patterns, and overlap with existing skills...

## visualization

- **[community]** `visualization/data-viz-storytelling-healy` — data-viz-storytelling-healy: >   Chọn đúng biểu đồ, kể chuyện với số liệu, và tránh误导 — dựa trên nguyên tắc   từ Kieran Healy (Data Visualization, Princeton 2019) và ...
- **[community]** `visualization/infographics` — infographics: Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Integrat...
- **[community]** `visualization/matplotlib` — matplotlib: Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot ty...
- **[community]** `visualization/scientific-visualization` — scientific-visualization: Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annota...
- **[community]** `visualization/seaborn` — seaborn: Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons...

## voltagent

- **[imported]** `voltagent` — voltagent-subagents: >-   Cursor skills converted from VoltAgent awesome-claude-code-subagents (DS/ML/AI/   research, product, orchestration). Use when you wa...
- **[imported]** `voltagent/business-product/business-analyst` — business-analyst: Use when analyzing business processes, gathering requirements from stakeholders, or identifying process improvement opportunities to driv...
- **[imported]** `voltagent/business-product/customer-success-manager` — customer-success-manager: Use this agent when you need to assess customer health, develop retention strategies, identify upsell opportunities, or maximize customer...
- **[imported]** `voltagent/business-product/product-manager` — product-manager: Use this agent when you need to make product strategy decisions, prioritize features, or define roadmap plans based on user needs and bus...
- **[imported]** `voltagent/business-product/project-manager` — project-manager: Use this agent when you need to establish project plans, track execution progress, manage risks, control budget/schedule, and coordinate ...
- **[imported]** `voltagent/business-product/scrum-master` — scrum-master: Use when teams need facilitation, process optimization, velocity improvement, or agile ceremony management\u2014especially for sprint pla...
- **[imported]** `voltagent/business-product/technical-writer` — technical-writer: Use this agent when you need to create, improve, or maintain technical documentation including API references, user guides, SDK documenta...
- **[imported]** `voltagent/business-product/ux-researcher` — ux-researcher: Use this agent when you need to conduct user research, analyze user behavior, or generate actionable insights to validate design decision...
- **[imported]** `voltagent/data-ai/ai-engineer` — ai-engineer: Use this agent when architecting, implementing, or optimizing end-to-end AI systems\u2014from model selection and training pipelines to p...
- **[imported]** `voltagent/data-ai/data-analyst` — data-analyst: Use when you need to extract insights from business data, create dashboards and reports, or perform statistical analysis to support decis...
- **[imported]** `voltagent/data-ai/data-engineer` — data-engineer: Use this agent when you need to design, build, or optimize data pipelines, ETL/ELT processes, and data infrastructure. Invoke when design...
- **[imported]** `voltagent/data-ai/data-scientist` — data-scientist: Use this agent when you need to analyze data patterns, build predictive models, or extract statistical insights from datasets. Invoke thi...
- **[imported]** `voltagent/data-ai/database-optimizer` — database-optimizer: Use this agent when you need to analyze slow queries, optimize database performance across multiple systems, or implement indexing strate...
- **[imported]** `voltagent/data-ai/llm-architect` — llm-architect: Use when designing LLM systems for production, implementing fine-tuning or RAG architectures, optimizing inference serving infrastructure...
- **[imported]** `voltagent/data-ai/machine-learning-engineer` — machine-learning-engineer: Use this agent when you need to deploy, optimize, or serve machine learning models at scale in production environments.
- **[imported]** `voltagent/data-ai/ml-engineer` — ml-engineer: Use this agent when building production ML systems requiring model training pipelines, model serving infrastructure, performance optimiza...
- **[imported]** `voltagent/data-ai/mlops-engineer` — mlops-engineer: Use this agent when you need to design and implement ML infrastructure, set up CI/CD for machine learning models, establish model version...
- **[imported]** `voltagent/data-ai/nlp-engineer` — nlp-engineer: Use when building production NLP systems, implementing text processing pipelines, developing language models, or solving domain-specific ...
- **[imported]** `voltagent/data-ai/postgres-pro` — postgres-pro: Use when you need to optimize PostgreSQL performance, design high-availability replication, or troubleshoot database issues at scale. Inv...
- **[imported]** `voltagent/data-ai/prompt-engineer` — prompt-engineer: Use this agent when you need to design, optimize, test, or evaluate prompts for large language models in production systems.
- **[imported]** `voltagent/data-ai/reinforcement-learning-engineer` — reinforcement-learning-engineer: Use when designing RL environments, training agents with reward optimization, implementing policy gradient methods, or deploying decision...
- **[imported]** `voltagent/dev-workflow/documentation-engineer` — documentation-engineer: Use this agent when you need to create, architect, or overhaul comprehensive documentation systems including API docs, tutorials, guides,...
- **[imported]** `voltagent/dev-workflow/git-workflow-manager` — git-workflow-manager: Use this agent when you need to design, establish, or optimize Git workflows, branching strategies, and merge management for a project or...
- **[imported]** `voltagent/dev-workflow/refactoring-specialist` — refactoring-specialist: Use when you need to transform poorly structured, complex, or duplicated code into clean, maintainable systems while preserving all exist...
- **[imported]** `voltagent/fintech-risk/fintech-engineer` — fintech-engineer: Use when building payment systems, financial integrations, or compliance-heavy financial applications that require secure transaction pro...
- **[imported]** `voltagent/fintech-risk/healthcare-admin` — healthcare-admin: Use when working on healthcare administration tasks including revenue cycle management, HIPAA/compliance auditing, medical coding (ICD-10...
- **[imported]** `voltagent/fintech-risk/quant-analyst` — quant-analyst: Use this agent when you need to develop quantitative trading strategies, build financial models with rigorous mathematical foundations, o...
- **[imported]** `voltagent/fintech-risk/risk-manager` — risk-manager: Use this agent when you need to identify, quantify, and mitigate enterprise-level risks across financial, operational, regulatory, and st...
- **[imported]** `voltagent/infra/deployment-engineer` — deployment-engineer: Use this agent when designing, building, or optimizing CI/CD pipelines and deployment automation strategies.
- **[imported]** `voltagent/languages/python-pro` — python-pro: Use this agent when you need to build type-safe, production-ready Python code for web APIs, system utilities, or complex applications req...
- **[imported]** `voltagent/languages/sql-pro` — sql-pro: Use this agent when you need to optimize complex SQL queries, design efficient database schemas, or solve performance issues across Postg...
- **[imported]** `voltagent/orchestration/context-manager` — context-manager: Use for managing shared state, information retrieval, and data synchronization when multiple agents need coordinated access to context an...
- **[imported]** `voltagent/orchestration/error-coordinator` — error-coordinator: Use this agent when distributed system errors occur and need coordinated handling across multiple components, or when you need to impleme...
- **[imported]** `voltagent/orchestration/knowledge-synthesizer` — knowledge-synthesizer: Use when you need to extract actionable patterns from agent interactions, synthesize insights across multiple workflows, and enable organ...
- **[imported]** `voltagent/orchestration/multi-agent-coordinator` — multi-agent-coordinator: Use when coordinating multiple concurrent agents that need to communicate, share state, synchronize work, and handle distributed failures...
- **[imported]** `voltagent/orchestration/task-distributor` — task-distributor: Use when distributing tasks across multiple agents or workers, managing queues, and balancing workloads to maximize throughput while resp...
- **[imported]** `voltagent/quality-engineering/code-reviewer` — code-reviewer: Use this agent when you need to conduct comprehensive code reviews focusing on code quality, security vulnerabilities, and best practices.
- **[imported]** `voltagent/quality-engineering/debugger` — debugger: Use this agent when you need to diagnose and fix bugs, identify root causes of failures, or analyze error logs and stack traces to resolv...
- **[imported]** `voltagent/quality-engineering/performance-engineer` — performance-engineer: Use this agent when you need to identify and eliminate performance bottlenecks in applications, databases, or infrastructure systems, and...
- **[imported]** `voltagent/quality-engineering/qa-expert` — qa-expert: Use this agent when you need comprehensive quality assurance strategy, test planning across the entire development cycle, or quality metr...
- **[imported]** `voltagent/research-analysis/competitive-analyst` — competitive-analyst: Use when you need to analyze direct and indirect competitors, benchmark against market leaders, or develop strategies to strengthen compe...
- **[imported]** `voltagent/research-analysis/data-researcher` — data-researcher: Use this agent when you need to discover, collect, and validate data from multiple sources to fuel analysis and decision-making. Invoke t...
- **[imported]** `voltagent/research-analysis/market-researcher` — market-researcher: Use this agent when you need to analyze markets, understand consumer behavior, assess competitive landscapes, and size opportunities to i...
- **[imported]** `voltagent/research-analysis/project-idea-validator` — project-idea-validator: Use this agent when you need an idea pressure-tested with brutal honesty, competitor teardown, market validation, and clear go/no-go guid...
- **[imported]** `voltagent/research-analysis/research-analyst` — research-analyst: Use this agent when you need comprehensive research across multiple sources with synthesis of findings into actionable insights, trend id...
- **[imported]** `voltagent/research-analysis/scientific-literature-researcher` — scientific-literature-researcher: Use when you need to search scientific literature and retrieve structured experimental data from published studies. Invoke this agent whe...
- **[imported]** `voltagent/research-analysis/search-specialist` — search-specialist: Use when you need to find specific information across multiple sources using advanced search strategies, query optimization, and targeted...
- **[imported]** `voltagent/research-analysis/trend-analyst` — trend-analyst: Use when analyzing emerging patterns, predicting industry shifts, or developing future scenarios to inform strategic planning and competi...

## writing-docs

- **[community]** `writing-docs/docx` — docx: Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention o...
- **[community]** `writing-docs/pdf` — pdf: Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combinin...
- **[community]** `writing-docs/pptx` — pptx: >   Create and edit PowerPoint presentations (.pptx)—slides, layouts, speaker notes,   and export. Use when the deliverable is a deck for...
- **[community]** `writing-docs/prose-polish` — prose-polish: >   Polish technical and stakeholder prose—clarity, tone, structure, and reducing   generic AI-writing patterns. Use for blog posts, know...
- **[community]** `writing-docs/scientific-writing` — scientific-writing: Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage p...
- **[community]** `writing-docs/sympy` — sympy: Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solvi...
- **[community]** `writing-docs/xlsx` — xlsx: Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit,...

