# Sleuth Skills - [Welcome to Sleuth Skills](https://help.sleuth.io/sleuth-skills/sleuth-skills.md): Sleuth Skills is where your team creates, reviews, and governs the AI assets — skills, rules, agents, commands, hooks, MCP servers, and Claude Code plugins — that make every engineer more productive. - [Quick Start Guide](https://help.sleuth.io/sleuth-skills/quick-start.md): Create your first AI asset, install it to a target, and verify it runs. This walkthrough takes about 10 minutes and covers setup, asset types, asset discovery, and asset distribution. - [Manage](https://help.sleuth.io/sleuth-skills/manage.md): Create, edit, version, and review the AI assets your org publishes — plus the RBAC model that controls who is allowed to do each of those things. - [RBAC](https://help.sleuth.io/sleuth-skills/manage/rbac.md): How role-based access control works in Sleuth Skills. Covers global admins, team admins, and the change-request flow that reviews edits and installation requests from regular members. - [Skills](https://help.sleuth.io/sleuth-skills/manage/skills.md): Skills are named capabilities with a prompt, metadata, and optional bundled reference files. The AI client loads a skill when its description matches the user's goal. - [Rules](https://help.sleuth.io/sleuth-skills/manage/rules.md): Rules are coding standards and guidelines that the client applies based on file type or path. Unlike skills, rules do not wait to be triggered — they're always on when their scope matches. - [Agents](https://help.sleuth.io/sleuth-skills/manage/agents.md): Agents are autonomous AI workers with a specific goal — reviewing a branch, writing tests, investigating a bug. Published agents become invokable from any installed client. - [Commands](https://help.sleuth.io/sleuth-skills/manage/commands.md): Commands are explicit slash commands the user types. They are the right tool when you want a named shortcut with predictable behavior, not a description-triggered skill. - [Hooks](https://help.sleuth.io/sleuth-skills/manage/hooks.md): Hooks are shell commands the client runs in response to lifecycle events — before a prompt, after a tool call, on session exit, and similar. - [MCP servers](https://help.sleuth.io/sleuth-skills/manage/mcp-servers.md): MCP servers package Model Context Protocol server definitions so the client can launch and talk to them. Use them to give AI clients structured access to internal APIs, databases, and custom tools. - [Claude Code plugins](https://help.sleuth.io/sleuth-skills/manage/claude-code-plugins.md): Claude Code plugins bundle skills, commands, hooks, and MCP configs into a single installable unit. Use them when a product feature needs all four types deployed together. - [Distribute](https://help.sleuth.io/sleuth-skills/distribute.md): Once an asset exists, Distribute is where you decide who gets it — your organization, a team, a repository, a bot, or an individual person. - [Organization](https://help.sleuth.io/sleuth-skills/distribute/organization.md): The root installation target. Every member of your Sleuth Skills vault belongs to exactly one organization; org-scoped installs reach everyone. - [Teams](https://help.sleuth.io/sleuth-skills/distribute/teams.md): Teams group members, bots, and repositories into a single unit. Installing an asset to a team cascades to every member, every bot, and every repository on the team. - [Repositories](https://help.sleuth.io/sleuth-skills/distribute/repositories.md): Repository installs attach an asset to a specific git repo. They apply only when sx install runs inside a clone of that repo, writing to the repo's local .claude/ directory. - [Bots](https://help.sleuth.io/sleuth-skills/distribute/bots.md): Bots are service accounts that can join teams and receive asset installs the same way users do. Use them for CI agents, scheduled loops, and review bots. - [Personal](https://help.sleuth.io/sleuth-skills/distribute/personal.md): Personal installs apply only to you. Use them to experiment with an asset before sharing it, or for tools that don't make sense for anyone else. - [Govern](https://help.sleuth.io/sleuth-skills/govern.md): Sleuth Skills keeps an append-only audit log of every install and team change, plus pre-built dashboards that show what your org is actually using. - [Audit log](https://help.sleuth.io/sleuth-skills/govern/audit-log.md): Every install, uninstall, team change, and asset mutation in Sleuth Skills is recorded in an append-only audit log. Use it for compliance reviews, incident reconstruction, and operational debugging. - [Usage metrics](https://help.sleuth.io/sleuth-skills/govern/metrics.md): Sleuth Skills ships pre-built dashboards for adoption, usage, and leaderboards. They tell you whether assets are actually being picked up, by whom, and in which repositories. - [API](https://help.sleuth.io/sleuth-skills/api.md): Sleuth Skills exposes both a REST API and a GraphQL API at app.skills.new. Use them to drive the same actions your engineers take in the web app — authoring assets, resolving installs, downloading bun - [Authentication](https://help.sleuth.io/sleuth-skills/api/authentication.md): Every Skills.new API call is authenticated and scoped to a single organization. The credential you pass determines whether the caller acts as a user, an org-level service account, or a bot. - [REST API](https://help.sleuth.io/sleuth-skills/api/rest.md): REST endpoints under /api/skills/ on app.skills.new. These are what sx install, sx update, and CI agents call to resolve and download assets. - [GraphQL API](https://help.sleuth.io/sleuth-skills/api/graphql.md): The GraphQL API at app.skills.new/graphql is the management surface used by the web UI — assets, bots, profiles, installations, change requests, audit log, and AI metrics. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://help.sleuth.io/sleuth-skills.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. 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