Anthropic

@anthropic · Anthropic · Public GitHub skills

United States of Americaanthropic.com

566 published Skills

Curated from public sources. This profile has not been claimed.

GitHub sources566 Skills · 17 repositories

17 sources

Catalog 566Comments

566 standalone skills566 published skills

Infrastructure

oncall-handoff

Run the oncall handoff for a rotation window — the whole handoff, not just a document: build the summary (what the incoming oncall needs to know first, what is still open, incidents with impact numbers, alert and page counts, hygiene suggestions, every number traceable to a source), post it as the report for the outgoing oncall to correct, walk the incoming oncall through the open items and answer their questions in the thread, update the open-items list as they respond, and note when the incoming person acknowledges. Runs mainly in the team's standing oncall / monitoring channel, normally as

AI Agents

incident-sitrep

Post a sitrep (situation report) for a live incident, in its incident channel: a short update in a fixed layout for people who have not read the whole channel — the current picture and what moved since the previous update, nothing more. Use on "sitrep", "status update", "where are we", "what's the latest", "catch me up", "summarize the incident so far", "update for leadership / support / customers", or when asked to keep posting one on a schedule ("post a sitrep every hour until this is resolved"); also when the oncall memory sets an update cadence for incidents of this severity and the person

Analytics

incident-postmortem

Write the postmortem for an incident, in its incident channel, once it is mitigated or resolved. Use on "write up this incident", "postmortem", "incident summary", "what happened here for people who weren't around", "draft the retro", or when the oncall memory says incidents of this severity get one. Reads the incident channel (and the alert thread it came from), the investigation findings and the data behind them, and writes a one-screen, zero-context write-up: what happened, impact with numbers, detection, timeline with durations, why it happened, what fixed it, follow-ups with proposed owne

Infrastructure

incident-investigate

Investigate an alert, page, or production symptom in an incident channel, or in a team's oncall / monitoring channel — in an alert's own thread, or under a top-level message reporting one — and report findings a human can verify. Ordinary conversation, questions, links and chatter are not alerts: leave those alone — a post that is clearly none of these does not select this skill outside a covered feed channel, where the sorting ladder judges it instead. Use when an alert or page lands, when error rate, latency, or saturation is up, when someone asks "why is X broken", "is this real", "is anyon

Infrastructure

incident-init

Automatic init the first time Claude acts in an incident or alerts channel — a channel named like #inc-…, #incident-…, #sev0-…/#sev1-…, or one whose recent messages are pages or alerts — posted by PagerDuty, Opsgenie, incident.io, Datadog, Sentry or Grafana, or typed by people relaying them; ordinary talk about having been paged is not an alert — and that is not already set up as a team's oncall / monitoring channel. Run it once per channel, on first contact (just invited, first @-mention, channel just created), before doing whatever was asked: load the oncall memory that oncall setup wrote to

Analytics

graphing

Compose polished charts (timeseries, bar, line, area, pie, scatter, or anything else the data calls for) from tabular data using the chartkit primitives, producing PNG, SVG, or self-contained interactive HTML. Use when the user asks to chart, graph, plot, or visualize data and wants something better than raw matplotlib defaults.

Backend

bigquery-api

Run SQL against Google BigQuery and browse its catalog — submit queries (sync or async), poll job status, page through results, list datasets/tables, and read table schemas. Use this whenever the user wants to query a BigQuery table, ask "what's in this dataset", check a BigQuery job's status, or mentions bigquery.googleapis.com or a `project.dataset.table` path. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

Backend

asana-api

Read and manage Asana tasks, projects, sections, comments, and workspaces. Use this whenever the user wants to list or search tasks, create or update a task, complete a task, comment on a task, move tasks between projects or sections, look up a project or workspace, or ask "what's on my Asana list" — even if they don't say "API". Also use it for any app.asana.com URL or an Asana task/project gid. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

Testing

verify

Build and drive the copilot-kit-ag-ui demo to verify changes end-to-end.

Testing

verify

Build the computer-use-demo image and drive the Streamlit UI headlessly to verify changes end-to-end.

AI Agents

first-run

Guide a new user through their first computer-use agent run (env check, safe browser-only task, then open the trajectory viewer).

AI Agents

session-report

Generate an explorable HTML report of Claude Code session usage (tokens, cache, subagents, skills, expensive prompts) from ~/.claude/projects transcripts.

AI Agents

receipts

Generate a personal Claude Code usage & impact report ("receipts") from this machine's local session transcripts — for justifying Claude Code usage/spend to a manager, self-review, or "what have I been using this for" check-ins. Mines ~/.claude/projects locally (no extra API calls beyond one final write-up), cross-references local git history, and writes a markdown report plus a self-contained HTML receipt to your home directory. Use when the user asks for "receipts", an "impact report", "usage report", wants to "show my Claude Code activity", "prove the value of Claude Code", or runs `/receip

AI Agents

project-artifact

Generate and publish a project status artifact — an opinionated, tabbed status page for a project too big for one update (overview & success criteria, the workstream sequence, next steps, plus background, plan, risks & open questions, and decisions/FAQ when they earn a tab) — published with the built-in Artifact tool to a default-private claude.ai page the user can share with teammates. Use when a piece of work spans several workstreams and you want a shareable overview kept current. Each artifact is backed by a small per-project config in the plugin data dir, so refreshing it re-gathers live

AI Agents

skill-development

This skill should be used when the user wants to "create a skill", "add a skill to plugin", "write a new skill", "improve skill description", "organize skill content", or needs guidance on skill structure, progressive disclosure, or skill development best practices for Claude Code plugins.

AI Agents

plugin-structure

This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.

AI Agents

plugin-settings

This skill should be used when the user asks about "plugin settings", "store plugin configuration", "user-configurable plugin", ".local.md files", "plugin state files", "read YAML frontmatter", "per-project plugin settings", or wants to make plugin behavior configurable. Documents the .claude/plugin-name.local.md pattern for storing plugin-specific configuration with YAML frontmatter and markdown content.

AI Agents

mcp-integration

This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.

AI Agents

hook-development

This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.

AI Agents

command-development

This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.

AI Agents

agent-development

This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

AI Agents

playground

Creates interactive HTML playgrounds — self-contained single-file explorers that let users configure something visually through controls, see a live preview, and copy out a prompt. Use when the user asks to make a playground, explorer, or interactive tool for a topic.

AI Agents

build-mcpb

This skill should be used when the user wants to "package an MCP server", "bundle an MCP", "make an MCPB", "ship a local MCP server", "distribute a local MCP", discusses ".mcpb files", mentions bundling a Node or Python runtime with their MCP server, or needs an MCP server that interacts with the local filesystem, desktop apps, or OS and must be installable without the user having Node/Python set up.

AI Agents

build-mcp-server

This skill should be used when the user asks to "build an MCP server", "create an MCP", "make an MCP integration", "wrap an API for Claude", "expose tools to Claude", "make an MCP app", or discusses building something with the Model Context Protocol. It is the entry point for MCP server development — it interrogates the user about their use case, determines the right deployment model (remote HTTP, MCPB, local stdio), picks a tool-design pattern, and hands off to specialized skills.