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Agent Skills

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biome

Lint and format frontend code with Biome 2.4. Covers type-aware linting, GritQL custom rules, domains, import organizer, and migration from ESLint/Prettier. Use when configuring linting rules, formatting code, writing custom lint rules, or setting up CI checks. Triggers on biome, biome config, biome lint, biome format, biome check, biome ci, gritql, migrate from eslint, migrate from prettier, import sorting, code formatting, lint rules, type-aware linting, noFloatingPromises.

tenequm
tenequm
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command-skill-creator

Create automation command skills (slash commands) for Claude Code projects. Use when building `/slash-commands` that automate multi-step workflows - deploys, commits, releases, migrations, cross-repo operations, or any repeatable process. Triggers on "create a command", "make a slash command", "automate this workflow", "turn this into a command", "build a command skill", or when designing phased execution skills with approval gates. For command-type skills (imperative prompts in `.claude/skills/`), NOT knowledge/reference skills.

tenequm
tenequm
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effect-ts

Effect-TS (Effect) comprehensive development guide for TypeScript. Use when building, debugging, reviewing, or generating Effect code. Covers typed error modeling (expected errors vs defects), structured concurrency (fibers), dependency injection (ServiceMap/Context + Layers), resource management (Scope), retry/scheduling (Schedule), streams, Schema validation, observability (OpenTelemetry), HTTP client/server, Effect AI (LLM integration), and MCP servers. Critical for AI code generation: includes exhaustive wrong-vs-correct API tables preventing hallucinated Effect code. Supports both Effect v3 (stable) and v4 (beta). Use this skill whenever code imports from 'effect', '@effect/platform', '@effect/ai', or the user mentions Effect-TS, typed errors with Effect, functional TypeScript with Effect, ServiceMap, Layer, or Schema from Effect. Also trigger when generating new TypeScript projects that could benefit from Effect patterns, even if the user doesn't explicitly name the library.

tenequm
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19

erc-8004

Build with ERC-8004 Trustless Agents - on-chain agent identity, reputation, validation, and discovery on EVM chains. Use when registering AI agents on-chain, building agent reputation systems, searching/discovering agents, working with the Agent0 SDK (agent0-sdk), or implementing the ERC-8004 standard. Triggers on ERC-8004, Agent0, agent identity, agent registry, agent reputation, trustless agents, agent discovery.

tenequm
tenequm
19

mcp-best-practices

Build production MCP servers with the TypeScript SDK. Covers spec 2025-11-25, SDK v1.28+/v2, transport selection, tool design, error handling, security, performance, and known bugs with workarounds. Use this skill whenever building MCP servers, designing MCP tools, choosing MCP transports, handling MCP errors, migrating to MCP v2, reviewing MCP security, optimizing MCP token usage, or working with registerTool, McpServer, streamable HTTP, outputSchema, structuredContent, or tool annotations.

tenequm
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mpp

Build with MPP (Machine Payments Protocol) - the open protocol for machine-to-machine payments over HTTP 402. Use when developing paid APIs, payment-gated content, AI agent payment flows, MCP tool payments, pay-per-token streaming, or any service using HTTP 402 Payment Required. Covers the mppx TypeScript SDK with Hono/Express/Next.js/Elysia middleware, pympp Python SDK, and mpp Rust SDK. Supports Tempo stablecoins, Stripe cards, Lightning Bitcoin, and custom payment methods. Includes charge (one-time) and session (streaming pay-as-you-go) intents. Make sure to use this skill whenever the user mentions mpp, mppx, machine payments, HTTP 402 payments, Tempo payments, payment channels, pay-per-token, paid API endpoints, or payment-gated services.

tenequm
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openclaw-ref

OpenClaw platform reference - plugin system, extensions, configuration, boot/provisioning, channels, models, CLI. Use when working on openclaw codebase, building openclaw plugins/extensions, configuring openclaw instances, provisioning openclaw gateways, designing agent provisioning flows (e.g. agentbox), or debugging openclaw config/plugin/channel issues. Triggers on openclaw, openclaw config, openclaw plugin, openclaw extension, openclaw channel, openclaw gateway, openclaw provisioning, openclaw onboarding, openclaw boot, openclaw skills, BOOT.md, openclaw.plugin.json, openclaw-x402, agentbox provisioning.

tenequm
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polish

Pre-release code review - runs lint/type checks, then launches 3 parallel review agents (cleanliness, design, efficiency) to analyze the diff, synthesizes a unified report, and fixes with approval. Use before committing, pushing, or releasing changes. Triggers on "review code", "check before commit", "cleanup before release", "review changes", "is this ready to ship", "polish before release", "simplify".

tenequm
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privy-integration

Integrate Privy authentication and wallet infrastructure into web and mobile apps. Covers React SDK setup (PrivyProvider, hooks, whitelabel auth), embedded wallets (EVM + Solana), smart wallets (ERC-4337), wagmi/viem integration, server-side Node.js SDK (@privy-io/node), token verification, gas sponsorship, external wallet connectors, and transaction signing. Use when building apps with Privy auth, creating embedded wallets, integrating web3 login, setting up wagmi with Privy, verifying Privy tokens on the server, sponsoring gas, or working with Privy's wallet API. Triggers on privy, privy auth, privy wallet, privy embedded wallet, privy login, privy react, privy wagmi, privy solana, privy smart wallet, privy server SDK, privy token verification, @privy-io/react-auth, @privy-io/node, @privy-io/wagmi, PrivyProvider.

tenequm
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python-dev

Opinionated Python development setup with uv + ty + ruff + pytest + just. Use when creating new Python projects, setting up pyproject.toml, configuring linting, type checking, testing, or build tooling. Triggers on "python project", "uv init", "pyproject.toml", "ruff config", "ty check", "pytest setup", "justfile", "python linting", "python formatting", "type checking python".

tenequm
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explain-concepts

Explains difficult concepts using master teaching methodologies (Feynman, Socratic, Cognitive Load, Dual Coding). Use when user asks to explain a concept, "I don't understand X", ELI5 requests, "what is X", "how does X work".

thepexcel
thepexcel
194

deep-research

Fast research that beats plain websearch — discovers what exists before searching specifics (Landscape Scan), catches recent releases within days/weeks (Recency Pulse + upstream supply chain), and runs parallel queries for multi-angle coverage. Good for everyday research and current-info questions. Use when user requests research, comparison, or "what's the latest on X". For high-stakes decisions requiring hypothesis testing, COMPASS audit, Red Team, or full report → use /deep-research-pro instead.

thepexcel
thepexcel
194

generate-creative-ideas

Creative problem-solving and ideation using SCAMPER, First Principles, Random Word, and AI-optimized techniques. Use when generating ideas, breaking creative blocks, brainstorming alternatives, or innovating.

thepexcel
thepexcel
194

rdkit

Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.

oimiragieo
oimiragieo
19

tauri-svelte-typescript-general

General rules for developing desktop applications using Tauri with Svelte and TypeScript for the frontend.

oimiragieo
oimiragieo
19

tauri-security-rules

Security-related rules for Tauri application development.

oimiragieo
oimiragieo
19

tauri-native-api-integration

Rules for integrating Tauri's native APIs in the frontend application.

oimiragieo
oimiragieo
19

task-management-protocol

Protocol for task synchronization, context handoff, and cross-session coordination using Claude Code task tools. Ensures agents properly update tasks with findings and enables seamless work continuation.

oimiragieo
oimiragieo
19

task-delegation

Agent task delegation patterns — spawn protocols, handoff metadata, drain gate, parallel limits, and model selection for multi-agent orchestration

oimiragieo
oimiragieo
19

static-analysis

Run CodeQL and Semgrep static analysis with SARIF output for vulnerability detection, code quality assessment, and security compliance scanning across multiple languages.

oimiragieo
oimiragieo
19

style-analyzer

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oimiragieo
oimiragieo
19

styling-expert

CSS and styling expert including Tailwind, CSS-in-JS, and responsive design

oimiragieo
oimiragieo
19

summarize-changes

Structured workflow for summarizing code changes after completing tasks. Creates clear, actionable summaries of what was changed, why, and what to verify.

oimiragieo
oimiragieo
19

svelte-expert

Svelte and SvelteKit expert including components, stores, and routing

oimiragieo
oimiragieo
19

swarm-coordination

Multi-agent swarm coordination patterns. Orchestrates parallel agent execution, manages agent communication, handles task distribution, and coordinates results aggregation.

oimiragieo
oimiragieo
19

system-health-check

Verifies repository baseline test passing state and available memory/GPU resources to ensure safe mission execution.

oimiragieo
oimiragieo
19

tall-stack-general

General guidelines for TALL stack development, emphasizing Laravel and PHP best practices.

oimiragieo
oimiragieo
19

visual-and-observational-rules

Defines the visual aspects of the game and how the player observes the world. This includes map color-coding, screen effects, and the overall simulation style.

oimiragieo
oimiragieo
19

verification-before-completion

Gate function preventing unverified completion claims. Use before claiming any task is done.

oimiragieo
oimiragieo
19

variant-analysis

Discover vulnerability variants by identifying similar code patterns across a codebase using CodeQL and Semgrep pattern matching, finding instances where a known bug class may recur.

oimiragieo
oimiragieo
19

user-flow-validator

Test user journey assertions against real surfaces (Web UI, CLI, API) with evidence collection and isolation boundaries

oimiragieo
oimiragieo
19

user-research

UX research methodology skill — usability testing protocols, user interview frameworks, persona development, journey mapping, heuristic evaluation (Nielsen's 10), A/B test analysis, accessibility auditing, and research synthesis using NNGroup methodology.

oimiragieo
oimiragieo
19

ui-components-expert

UI component library expert including Chakra, Material UI, and Mantine

oimiragieo
oimiragieo
19

uat-verify

Verify completed work against acceptance criteria, collect evidence, and produce a PASS/FAIL UAT report

oimiragieo
oimiragieo
19

typescript-expert

TypeScript and JavaScript expert including type systems, patterns, and tooling

oimiragieo
oimiragieo
19

tts-generation

AI text-to-speech generation using OpenAI TTS, ElevenLabs, and Google TTS backends. Converts text to audio files with voice selection, speed control, and format options.

oimiragieo
oimiragieo
19

tsconfig-json-rules

Defines general rules for tsconfig.json. It suggest using strict TypeScript checks

oimiragieo
oimiragieo
19

troubleshooting-regression

Regression troubleshooting workflow for hook/router/memory/search failures with enforced evidence and fix validation

oimiragieo
oimiragieo
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transcription

Audio and video transcription using Whisper AI via the transcribe-anything package. Supports local files, YouTube URLs, and microphone input with multiple backends (faster-whisper, openai-whisper, Whisper API).

oimiragieo
oimiragieo
19

scientific-writing

Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process with (1) section outlines with key points using research-lookup then (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.

oimiragieo
oimiragieo
19

scikit-bio

Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.

oimiragieo
oimiragieo
19

scikit-learn

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.

oimiragieo
oimiragieo
19

scikit-survival

Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.

oimiragieo
oimiragieo
19

scvi-tools

Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.

oimiragieo
oimiragieo
19

seaborn

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.

oimiragieo
oimiragieo
19

shap

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

oimiragieo
oimiragieo
19

simpy

Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.

oimiragieo
oimiragieo
19

stable-baselines3

Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.

oimiragieo
oimiragieo
19

statistical-analysis

Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.

oimiragieo
oimiragieo
19

statsmodels

Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.

oimiragieo
oimiragieo
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Adoption

Agent Skills are supported by leading AI development tools.

FAQ

Frequently asked questions about Agent Skills.

01

What are Agent Skills?

Agent Skills are reusable, production-ready capability packs for AI agents. Each skill lives in its own folder and is described by a SKILL.md file with metadata and instructions.

02

What does this agent-skills.md site do?

Agent Skills is a curated directory that indexes skill repositories and lets you browse, preview, and download skills in a consistent format.

03

Where are skills stored in a repo?

By default, the site scans the skills/ folder. You can also submit a URL that points directly to a specific skills folder.

04

What is required inside SKILL.md?

SKILL.md must include YAML frontmatter with at least name and description. The body contains the actual guidance and steps for the agent.

05

How can I submit a repo?

Click Submit in the header and paste a GitHub URL that points to a skills folder. We’ll parse it and add any valid skills to the directory.