Agent Skills

scan-new-specs

★ 119

by warpdotdev

Scan warpdotdev/warp and warp-server for recently merged PRODUCT.md specs that don't yet have a corresponding docs PR in warpdotdev/docs. When a complete spec is found, auto-generates a full docs draft PR and tags the engineer. When a spec is too thin to draft from, pings the engineer directly. Designed to run as a scheduled Oz ambient agent (e.g., every 2-3 days). Use when setting up the automated docs trigger or running a manual docs coverage sweep.

cross-critique

★ 119

by warpdotdev

Run a second round on a contested question by circulating each subagent's independent proposal to the other authors and asking for structured pros and cons, then synthesize. Use this skill whenever you have multiple independent proposals or opinions on a contested decision — architecture tradeoffs, code review disagreements, design choices, competing root-cause theories — and want sharper analysis than you'd produce by synthesizing alone. Pairs naturally with the council and research skills; rea

research

★ 119

by warpdotdev

Delegate noisy investigation to one or more subagents so the orchestrator's context stays clean, then work from the distilled answer. Use this skill whenever answering a question would require reading many files, long logs, large diffs, or wide codebase surveys — i.e. when producing the answer generates far more noise than the answer itself. Use it for "how does X work", "where is Y used", "what's the root cause of Z", "summarize this PR/log" style questions, and reach for it liberally before re

deep-agents-orchestration

★ 108

by langchain-ai

INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.

langchain-oss-primer

★ 108

by langchain-ai

ALWAYS START HERE for any LangChain, Deep Agents, or LangGraph agent building project. Required starting point before choosing other skills or writing any code. Covers framework selection (LangChain vs LangGraph vs Deep Agents), agent archetypes, dependency setup, and which skills to load next based on your decisions.

deep-agents-core

★ 108

by langchain-ai

INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.

langchain-rag

★ 108

by langchain-ai

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

framework-selection

★ 108

by langchain-ai

INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.

langchain-dependencies

★ 108

by langchain-ai

INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.

deep-agents-memory

★ 108

by langchain-ai

INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.

langsmith-dataset

★ 108

by langchain-ai

INVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (final_response, single_step, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.

ecosystem-primer

★ 108

by langchain-ai

INVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent patterns, install, environment setup, and which skill to load next.

http-toolkit-intercept

★ 90

by factory-ai

Intercept and debug HTTP traffic from any CLI, service, or script using HTTP Toolkit. Use when you need to inspect LLM API calls, backend requests, auth flows, or debug network-level issues across any language or runtime.

no-use-effect

★ 90

by factory-ai

Enforce the no-useEffect rule when writing or reviewing React code. ACTIVATE when writing React components, refactoring existing useEffect calls, reviewing PRs with useEffect, or when an agent adds useEffect "just in case." Provides the five replacement patterns and the useMountEffect escape hatch.

init

★ 90

by factory-ai

Initialize a new repository with AGENTS.md

audit-clerk-skill

★ 54

by clerk

Audits the bundled `clerk-cli` skill against the Clerk CLI source tree and proposes or applies updates. Use when the user says "audit the clerk-cli skill", "update the clerk-cli skill", "check clerk-cli against the CLI source", "resync clerk-cli skill", "run audit-clerk-skill", or after Clerk CLI commands, flags, or agent-mode behavior change.

plugin-transfer

★ 14

by sanity-io

Guides agents through migrating an existing plugin into this monorepo with the copy-plugin generator workflow.

find-skills

★ 14

by sanity-io

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.