Skills
97,725 packaged capabilities and playbooks for agents. Install any of them with one command.
Agent workflows
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines
Use the public `aio-ade` CLI to operate AIO-ADE-managed worktrees, folder contexts, terminals, repos, automations, worktree comments, and the browser embedded inside the AIO-ADE app. Use when the user says "$aio-ade-cli", "use aio-ade cli", "AIO-ADE worktree", "child worktree", "cardStatus", "spawn codex/claude in a worktree", "read/wait/send AIO-ADE terminal", "terminal send", "full handoff", "handover", "give this to another agent", "another worktree", "AIO-ADE browser", or "control the browser inside AIO-ADE". Prefer this over raw `git worktree`, ad hoc PTYs, Playwright, or Computer Use when the task touches AIO-ADE-managed state. Use Computer Use for browser windows, webviews, or desktop UI outside AIO-ADE's embedded browser.
Сборка графа: узор над полем вопрошания и деятельности → 形, карта превращений; оценка телоса превращений. Триггеры: «собери граф», «сборка», «пересборка», «что здесь по сути происходит», «повестка», «превращение достигнуто?», «закрыть превращение», «пересмотри превращения», «что с этим превращением», assemble the realm, reassemble, map the transformations. Также: много свободных вимарш, стена top-level крий; существенный результат, приёмка перехода, смена замысла. Не weaving, design, inquiry. Нужны iskron_*.
Find the mistakes agents keep repeating in this repo and make each one impossible. Try architecture first, then types, then a lint whose error names the fix, then a test, and write docs last. Prove each check fails on a real past mistake. Repeat this each time the operator corrects you. Use for /correct.
Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3 Pro, Kimi K2, GLM-4.6, Intellect 3. One API for all models with automatic fallback and cost optimization. Use for: AI assistants, code generation, reasoning, agents, chat, content generation. Triggers: claude api, openrouter, llm api, claude sonnet, claude opus, gemini api, kimi, language model, gpt alternative, anthropic api, ai model api, llm access, chat api, claude alternative, openai alternative
Use when working on the methodology graph itself — not applying the methodology to a project, but its evolution. Triggers: methodology realm, "работа над методологией", "обогатить методологию", "methodology нужно дополнить", "записать принцип", "новая нить", references to the methodology graph by name, agent feedback about gaps in the methodology. Distinct from design (external systems) and weaving (semantic repair). Meta-work: methodology applied to itself. Highest stakes: every node shapes the thinking of future agents.
Scaffold a new brooks-lint analysis skill so it passes `npm run validate` and `npm run evals` on the first try — generates skills/{name}/SKILL.md (with the mandatory "Do NOT trigger for:" clause and a Process section citing guide step ranges) plus skills/{name}/{name}-guide.md (sequentially numbered steps), then appends paired eval scenarios. Triggers when the maintainer asks to "add a new skill", "scaffold a skill", or "create a brooks-lint mode". Do NOT trigger for: editing an existing skill's content, adding a single eval to an existing skill, or authoring skills for some other plugin.
This skill should be used when the user asks to "validate plugin structure", "review manifest files", "check frontmatter compliance", "verify tool invocation patterns", "explain plugin component types", or needs Claude Code plugin architectural guidance.
Set up and maintain a structured project memory system in docs/project_notes/ that tracks bugs with solutions, architectural decisions, key project facts, and work history. Use this skill when asked to "set up project memory", "track our decisions", "log a bug fix", "update project memory", or "initialize memory system". Configures both CLAUDE.md and AGENTS.md to maintain memory awareness across different AI coding tools.
Python SDK for inference.sh - run AI apps, build agents, and integrate with all models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip install, python api, python client, async inference, python agent, tool builder python, programmatic ai, python integration, sdk python
Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.
Manage durable working-session memory for coding agents. Use when a user asks to preserve or recover agent context across disconnects, VS Code restarts, long-running work, handoffs, or any session where important state should be written periodically under the repo's session directory. Do NOT use for: simple questions, short tasks, one-off commands, linting, or code review.
Personalized audit that teaches advanced Superset features the user isn't using yet — automations, parallel agents, tasks, multi-host, terminals, custom commands, MCP. Use when the user wants to get more out of Superset, learn advanced Superset features, or 10x their Superset workflow.
Turn a recurring chore into a Superset automation — drafts the agent prompt, confirms schedule and target, creates it with the CLI, and reviews the first run together. Use when the user wants a scheduled or recurring agent, a daily/weekly job, or to automate a repeating task with Superset.
Make a repository Superset-ready — author .superset/config.json with setup/teardown/run scripts so every new workspace boots configured, then verify with a real workspace. Use when the user wants to set up a project or repo for Superset, configure workspace setup scripts, or fix a failing workspace setup.
Validates hook, skill, and agent counts are consistent across CLAUDE.md, hooks.json, manifests, and source directories. Use when counts may be stale after adding or removing components, before releases, or when CLAUDE.md Project Overview looks wrong.
Design and write deterministic multi-agent workflow scripts (.js files in .claude/workflows/) for Claude Code's Workflow tool. Use when a user wants to build, create, author, scaffold, or run a custom Claude Code workflow, orchestrate sub-agents (fan-out, pipeline, loop, judge-panel), or automate a repeatable multi-step task across fresh-context agents.
Create, revise, review, and audit outgoing prompts for another agent or conversation. Validate incoming findings and status reports. Use for external task delegation prompts, explicitly requested subagent prompts, transfers of established results or decisions, and pasted review, audit, or status reports, including unframed reports. Don’t use merely to run or orchestrate autonomous in-client or CLI subagents. Exclude archival, explicitly deferred, illustrative, or incidental reports, and outdated reports unless the user requests reassessment.
Turn a vague request, voice dump, rough plan, or half-written prompt into a self-contained prompt that a fresh agent can execute. Use when asked to clarify, refine, improve, tighten, or stress-test an agent task. Resolve safe defaults directly. Ask one question at a time only when the answer would materially change the work.
Build heads-up display (HUD) dashboards for AI coding agents — show context usage, active tools, running sub-agents, and task progress in real-time. Use when: monitoring AI agent activity, building developer tools for AI-assisted coding, creating status dashboards for agent workflows.
Expert knowledge of GitHub Copilot CLI - installation, configuration, usage, MCP servers, skills, custom agents, and troubleshooting. Use when asking about copilot cli, installing copilot, gh copilot, copilot commands, MCP setup, or copilot extensibility.
Write an implementation plan as one interactive HTML page - a tree of claims (why › what › how › where), each proved by one exhibit (UI mockup, state machine, call stack, schema or code), with the decisions the user has to make placed on the claim they change. Use when the user types /html-plan, or asks for a plan, RFC or design before building something that touches more than a couple of files.
Use when writing Python code that imports from `inkbox`, uses `pip install inkbox`, or when adding email, mailbox imports, phone, text/SMS, iMessage, A2A task/message history, contacts, notes, contact rules, vault, tunnels, mailbox storage, mail clients (IMAP/SMTP), or agent identity features using the Inkbox Python SDK.
Use to let an EXTERNAL WORD into the Iskron graph — shabda intake; third-party text is checked against the graph and matters before being passed to a matter. Triggers: «впусти внешнее слово», «засей граф из issue/доков», «внеси issue», «запиши пост», «внеси новость», «разнеси чужой разбор по делам», intake, ingest issues, shabda intake. A source enters through an adapter; the discipline is the same. Distinct from writing (a completed distinction), assistant (a person's word verbatim), feedback (experience about the method), iskronify (derived config), product-roadmap (GitHub adapter). Requires the iskron_* tools.
JavaScript/TypeScript SDK for inference.sh - run AI apps, build agents, integrate with all models. Package: @inferencesh/sdk (npm install). Full TypeScript support, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, human approval. Use for: JavaScript integration, TypeScript, Node.js, React, Next.js, frontend apps. Triggers: javascript sdk, typescript sdk, npm install, node.js api, js client, react ai, next.js ai, frontend sdk, @inferencesh/sdk, typescript agent, browser sdk, js integration
Convert a local skill into a Claude Code optimized shape — an AUDIT-then-rewrite that ties every change to real Claude skill-runtime behavior, treating FRONTMATTER as the highest-leverage routing surface. Inventories the skill, checks it against the runtime reference (Claude routes and budgets skills from metadata first), writes a per-skill DAG rewrite plan with source-backed guardrails, and — only when asked — rewrites frontmatter, body, and references for cheaper routing and safer execution. Defaults to PLAN mode, never a blind rewrite, uses skill-native frontmatter only, and preserves structural content (routing tables, guardrail rules) rather than stripping it as bulk. Use to migrate or restructure a SKILL.md for Claude's skill runtime.
Use the public `orca` CLI to operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and the browser embedded inside the Orca app. Use when the user says "$orca-cli", "use orca cli", "Orca worktree", "child worktree", "cardStatus", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "terminal send", "full handoff", "handover", "give this to another agent", "another worktree", "Orca browser", "orca artifacts", "share HTML/Markdown", "public artifact link", "share skills", or "control the browser inside Orca". Prefer this over raw `git worktree`, ad hoc PTYs, Playwright, or Computer Use when the task touches Orca-managed state. Use Computer Use for browser windows, webviews, or desktop UI outside Orca's embedded browser.
Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.