Agent Skills
Instruction packs that give your AI agent know-how — some work anywhere, some only with the tool they came with.
✦ Standalone skills2,599
Self-contained. Install one into any project and it works on its own — no other software needed.
🧰 Tool add-ons428
Come bundled with a specific tool and only work together with it — they teach your agent how to operate that tool.
🔌 Needs setup first94
Each relies on something you set up separately — such as an app, a command-line tool or an account — and its page names what that is.
upstash
2,599 standalone skillsagentic-wallet
★ 120by coinbase
Crypto wallet operations via the awal CLI — sign in, check balances, send USDC/ETH/POL/SOL, trade tokens, fund the wallet, and use the x402 payment protocol to discover paid services, pay for API calls, monetize an API, or query onchain data. Use whenever the user mentions signing in, login, authentication, wallet status, balance, address, sending money, paying someone, transferring tokens, ENS names, swapping/trading/converting tokens, funding/topping up/onramp, USDC, ETH, POL, SOL, the x402 bazaar, paid APIs, monetizing an endpoint, or querying onchain data on Base.
respond-to-pr-comments-in-blocklist
★ 119by warpdotdev
Walk users through PR review comments, fetching and displaying them first when needed, collect per-comment response decisions, apply requested fixes, and preview GitHub replies and resolutions before posting. Use when responding to PR review comments on the current branch.
logging-best-practices
★ 119by boristane
Logging best practices focused on wide events (canonical log lines) for powerful debugging and analytics
update-skill
★ 119by warpdotdev
Create or update skills by generating, editing, or refining SKILL.md files in this repository. Use when authoring new skills or revising the structure, frontmatter, or guidance for existing ones.
write-feature-docs
★ 119by warpdotdev
Draft a complete documentation page for a new Warp feature from its PRODUCT.md and/or TECH.md spec. Use when an engineer has written a spec and needs to produce a first-pass MDX draft for the warpdotdev/docs repo. Also handles features without specs by researching the codebase first. Invoke this skill whenever an engineer mentions writing docs for a feature, drafting a docs page, creating feature documentation, starting the eng-docs workflow, or converting a spec into documentation. Requires an interactive session with the engineer present - it confirms a content design plan, then an outline, before drafting, and cannot run unattended. For automated, release-triggered docs, use the missing_docs skill in warpdotdev/docs instead. Works from warp-internal or warp-server.
council
★ 119by warpdotdev
Run a model-diverse subagent council to investigate the same problem from multiple perspectives, compare findings, and produce a final recommendation. Use this skill whenever the user asks for a council, second opinions, multiple agents/models to evaluate one question, parallel investigation, red-team/blue-team comparison, or help deciding between competing technical approaches.
resolve-merge-conflicts
★ 119by warpdotdev
Resolve Git merge conflicts by extracting only unresolved paths, conflict hunks, and compact diffs instead of loading whole files into context. Use when a merge, rebase, cherry-pick, or stash pop stops on conflicts, when `git status` shows unmerged paths, or when files contain conflict markers.
saga
★ 119by warpdotdev
Run an autonomous, spec-driven development "saga" for medium-to-large features using an orchestrator agent and a fleet of worker subagents. Use this skill whenever the user invokes /saga, asks to autonomously build a sizable feature end-to-end with minimal human intervention, wants a comprehensive spec broken into milestones and tasks with airtight validation criteria before parallelized implementation, or wants an orchestrator to delegate implementation to worker agents while preserving its own context window. Trigger on phrases like "run a saga", "autonomously implement this feature", "spec it out then build it with subagents", "orchestrate this big feature end-to-end", or "build this with workers and validate each step". Also use this skill when asked to continue, resume, or pick up an existing saga from its saga directory (e.g. under ~/.sagas).
fix-errors
★ 119by warpdotdev
Fix compilation errors, linting issues, and test failures in the warp Rust codebase. Covers presubmit checks, WASM-specific errors, and running specific tests. Use when the user hits build errors, clippy or fmt failures, test failures, or needs to run or interpret presubmit before a PR.
reproduce-bug-report
★ 119by warpdotdev
Launch Oz cloud agents with computer use to reproduce UI-focused bug reports, capture visual evidence, and report reproduction findings. Use when investigating a specific interactive or visual bug from an issue, ticket, support report, or prompt.
diagnose-ci-failures
★ 119by warpdotdev
Diagnose CI failures for a PR using the GitHub CLI, extract error logs, and generate a plan to fix them. Use when the user asks to check CI status, pull CI issues, triage test failures, or investigate PR build failures.
pr-walkthrough
★ 119by warpdotdev
Generate a static interactive D3 walkthrough of a pull request. Use when the user wants a zoomable PR map, graph/canvas PR orientation, or alternate visualization of PR system components, data flow, code dependencies, and user actions.
research
★ 119by 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 reading a pile of files inline.
scan-new-specs
★ 119by 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.
validate-changes-match-specs
★ 119by warpdotdev
Validate that a branch or pull request implementation matches introduced product, technical, security, and related specs. Use when reviewing or finishing a spec-driven change and resolving mismatches between checked-in specs and implementation.
spec-driven-implementation
★ 119by warpdotdev
Drive a spec-first workflow for substantial features by writing PRODUCT.md before implementation, writing TECH.md when warranted, and keeping both specs updated as implementation evolves. Use when starting a significant feature, planning agent-driven implementation, or when the user wants product and tech specs checked into source control.
cross-critique
★ 119by 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; reach for it liberally whenever proposals diverge.
check-impl-against-spec
★ 119by warpdotdev
Compare a pull request's implementation against spec context in spec_context.md and feed any material mismatches into review.json. Use during PR review when approved or repository spec context is available.
agent-tui
✓★ 118by pproenca
Automate terminal UI (TUI) apps with agent-tui for testing, inspection, demos, and scripted interactions. Use when automating CLI/TUI flows, regression testing terminal apps, verifying interactive behavior, or extracting structured text from terminal UIs. Also use when asked what agent-tui is, how it works, or to demo it. Do not use for web browsers, GUI apps, or non-terminal interfaces.
ecosystem-primer
★ 108by 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.
langgraph-human-in-the-loop
★ 108by langchain-ai
INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.
langgraph-persistence
★ 108by langchain-ai
INVOKE THIS SKILL when your LangGraph needs to persist state, remember conversations, travel through history, or configure subgraph checkpointer scoping. Covers checkpointers, thread_id, time travel, Store, and subgraph persistence modes.
react-components
★ 108by langchain-ai
Modern React component patterns with hooks and TypeScript
deep-agents-orchestration
★ 108by 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
★ 108by 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
★ 108by 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
★ 108by 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
★ 108by 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.
langgraph-fundamentals
★ 108by langchain-ai
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
testing-patterns
★ 108by langchain-ai
Unit testing and integration testing best practices