Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Agent workflows
Run a coding agent in an autonomous loop via a /ralph command, gated by a preflight check that every CLI is installed, linked, and authenticated. Use when driving long-running autonomous development from a wide, outcome-focused prompt.
Use when a task is too large for one model pass, needs parallel research or generation across many subtasks (like researching a dozen competitors at once), or the user asks to orchestrate multiple models, split work across a model team, run an advisor-worker loop, have a stronger model review the plan while cheap workers execute, or says "too big for one model" or "fan this out". Not for single-file edits or tasks one model handles in one pass.
Mark the current conversation as a durable handoff so a new agent can resume the work. Use when the user wants to preserve state for a later or parallel session. Triggers include "hand this off", "write a handoff", "drop a wheypoint", "checkpoint this", "compact the conversation", and "/wheypoint". Also use for "wrap up" or "I need to clear context" during a task. Do NOT use for phase handoffs from `/cook`, `/press`, `/age`, or `/cure`.
Run the cold-start interview to learn your commercial contracts practice and write your team practice profile. Use on first use of the plugin, when `~/.claude/plugins/config/claude-for-legal/commercial-legal/CLAUDE.md` is missing or still contains template placeholders, or when the user says "set up the plugin", "configure commercial contracts", "onboard me", or "let's get started". This is the only skill that should run on a fresh install.
Use the internet: search, read, and interact with 13+ platforms including Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu (小红书), Douyin (抖音), WeChat Articles (微信公众号), LinkedIn, Boss直聘, RSS, Exa web search, and any web page. Use when: (1) user asks to search or read any of these platforms, (2) user shares a URL from any supported platform, (3) user asks to search the web, find information online, or research a topic, (4) user asks to post, comment, or interact on supported platforms, (5) user asks to configure or set up a platform channel. Triggers: "搜推特"、"搜小红书"、"看视频"、"搜一下"、"上网搜"、"帮我查"、"全网搜索"、"search twitter"、"read tweet"、"youtube transcript"、"search reddit"、"read this link"、"看这个链接"、"B站"、"bilibili"、"抖音视频"、"微信文章"、"公众号"、"LinkedIn"、"GitHub issue"、"RSS"、"search online"、"web search"、"find information"、"research"、"帮我配"、"configure twitter"、"configure proxy"、"帮我安装".
Apply substantive quality and reliability grading to Ane's MEL/SRHR system (Ann/Vi/Li/Researcher team + wiki + harness + three-repo architecture): letter grades on 9 components and 10 dimensions plus OECD-DAC adapted criteria, three concrete risks, what an external evaluator would still want, and recommendations for moving the grade, with a mandatory self-grading bias note. Use when Ane types /grade-system, /grade, /quality-grade, /rate-system, or asks how good the system is. Honest grading, not flattery. Different from /system-audit (finds specific issues to fix; this grades overall quality posture).
Defragment and reorganize agent memory files: split bloated files, merge duplicates, remove stale information, and restructure the memory hierarchy. Use when memory files have grown unwieldy, contain redundancies, or need reorganization. Run periodically (weekly) or on demand.
Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Includes memory architecture with pre-compaction flush (so context survives when the window fills), reverse prompting (surfaces ideas you didn't know to ask for), security hardening, self-healing patterns (diagnoses and fixes its own issues), and alignment systems (stays on mission, remembers who it serves). Battle-tested patterns for agents that learn from every interaction and create value without being asked.
Recover actionable context from local `.claude` session artifacts and continue interrupted work without running `claude --resume`. This skill should be used when the user provides a Claude session ID, asks to continue prior work from local history, or wants to inspect `.claude` files before resuming implementation.
Get a fast, cheap, typed judgment over text or JSON from the jev CLI — a yes/no probability, one choice among labels, or an ordinal score — bare calibrated answers, never prose or explanations. Runs now from a shell or agent, in bulk (one decision per line) and in pipelines (exit codes, semantic grep). Use to classify, triage, route, screen, rank, filter or bulk-label items such as emails, customer feedback, chat or group messages, tweets, logs, git diffs or user requests, and as a cheap pre-filter before expensive LLM reading, a guardrail check, or a model/agent router. Applies to: classification, filtering, triage, routing, scoring, yes/no judgments, bulk labeling, semantic filtering — conclusions only, no explanations. Not for judgments that must come with an explanation, analysis or a written reply; not for writing, summarizing or extracting text; not for math or date arithmetic. To design or code a TypeSafe integration inside an application, use the official `typesafe-ai` skill. Unofficial; calls TypeSafe's Jev model through the TypeSafe API (default) or OpenRouter.
Set up a hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, or when the user asks to set up AGENTS.md, add an intent layer, make agents understand the codebase, or scaffold AI-friendly project documentation.
Turns marketing prompts into tested, versioned production assets: A/B prompt evaluation against structured test cases, immutable prompt version history with diffs, ready-to-use marketing prompt templates (ad copy, email campaigns, social posts, landing pages, SEO meta), and an LLM-governance playbook for marketing teams (claim discipline, disclosure rules, human-review gates). Use when a marketing team relies on AI-generated content and needs prompt quality to be measurable and safe — or when the user mentions 'prompt engineering,' 'improve my prompts,' 'prompt templates,' 'prompt versioning,' 'AI content workflow,' or 'AI governance for marketing.'
Check installed community skills for updates. Shows a diff and requires explicit approval before applying. Use when the user says "check for updates", "update my skills", "anything new for my installed skills", or when invoked from the registry-sync agent.
Use when creating cloud sandboxes (microVMs) to run code, start dev servers, and generate live preview URLs. Also covers deploying AI agents, MCP servers, batch jobs, and Agent Drives (shared filesystems) on Blaxel's serverless infrastructure. Reach for this skill when you need isolated compute environments, real-time app previews, shared file storage across sandboxes, or to deploy agentic workloads.
Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.
Retrieve and apply OpenViking Experience memories through the Agent runtime's generic OpenViking search and read tools. Use before or during executable, multi-step, or tool-based work such as coding, file or data changes, configuration, deployment, workflow execution, and failure recovery when prior operational guidance could improve reliability. Do not use for casual chat or simple factual questions.
Use the public `orca` CLI to operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, 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", 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.
Use this skill for code reviews with the Codex CLI from a Claude-hosted session. Activates on mentions of codex review, code review with codex, codex check, gpt review, codex exec review, run codex, review my code, review this PR, review changes, peer review, or second opinion.
Validate, test, and score the quality of skills within the claude-skills ecosystem. Comprehensive meta-skill: structure validation, Python script testing (syntax + imports + runtime + output format), multi-dimensional quality scoring with letter grades and tier classification (BASIC/STANDARD/POWERFUL). Use when authoring a new skill, auditing existing skills for tier promotion, setting up pre-commit hooks for skill quality, or integrating skill QA into CI
Use this skill when exploring an open product or architecture question before choosing an approach. Activates on mentions of brainstorm, ideate, design session, explore options, what should we build, how should we approach, let's think about, new project, architecture decision, or design exploration. Skip it for a clear implementation request.
Build visual conversation workflows in Vapi with nodes for conversation steps, tool execution, conditional branching, and handoffs. Use when creating structured multi-step voice interactions that need deterministic flow control beyond what a single assistant prompt provides.
Review and approve (or reject) pending playbook update proposals from the playbook-monitor agent and apply approved changes to the practice profile. Use when the playbook-monitor agent has surfaced proposals, when the user says "review playbook proposals", "what playbook updates are pending", or wants to step through deviation-driven playbook changes.
Run a repo-wide cross-cutting governance audit via the pm-skill-auditor sub-agent. Aggregates the enforcing validator suite, re-derives aggregate counters, and surfaces cross-cutting issues no single validator catches, graded P0/P1/P2/P3 with a machine-readable status. Use for pre-release readiness checks or a periodic repo health audit.
Multi-agent board meeting protocol for strategic decisions. Runs a structured 6-phase deliberation: context loading, independent C-suite contributions (isolated, no cross-pollination), critic analysis, synthesis, founder review, and decision extraction. Use when the user invokes /c-level-agents:boardroom, calls a board meeting, or wants structured multi-perspective executive deliberation on a strategic question.
Guided customization of your commercial contracts practice profile — change one thing without re-running the whole cold-start interview. Adjust risk posture, escalation contacts, playbook positions, NDA triage preferences, house style, review preferences, or matter workspace paths. Use when the user says "change my [thing]", "update my profile", "edit my playbook", "tune my config", or "customize".
Evaluate a skill against the Legal Skill Design Framework — thirteen design parameters (including trust-surface, freshness, schema validation, and conflict detection), three legal failure modes, and a three-band verdict (Ready / Some Concern / Material Concerns). Use when deciding whether to trust a community skill before installing it, before deploying a first-party skill to your team, or whenever the user asks "should I trust this?" or "is this skill well-designed?". Runs automatically as part of /legal-builder-hub:skill-installer.
Use when building custom agent backends, implementing the AG-UI protocol, debugging streaming issues, or understanding how agents communicate with frontends. Covers event types, SSE transport, AbstractAgent/HttpAgent patterns, state synchronization, tool calls, and human-in-the-loop flows.
Community edition of the deep research agent system. Performs multi-round iterative web search and comprehensive analysis on complex topics. Use case: when the user needs in-depth, comprehensive research on a specific topic, especially when a detailed analysis report based on the latest web information is required. Supports multi-round iterative search, intelligent adjustment of search direction, and generation of comprehensive analysis reports. This skill is a workflow description document with no execution scripts; it relies on the web-search skill for web search.
Reference: detailed uninstall, disable, and re-enable workflows for community skills installed via the legal builder hub. Safe by default — refuses to touch first-party plugin skills, confirms before removing files, and logs every action. Loaded by the /legal-builder-hub:uninstall and /legal-builder-hub:disable skills.
Capture a claude.ai Desktop session into the MEL file system. Use when Ane finishes a session in the Claude Desktop app and wants the work captured on the device — triggered by "/capture-desktop", "capture this desktop session", "I did this on Claude desktop", "save my desktop work", "import from claude.ai". Paste-driven; no cloud API exists. Stages a local transcript, classifies content into deliverables, decisions/rules, project-knowledge changes, and full log, then files each to its home. Auto-files transcript + deliverables; confirms memory/wiki/CLAUDE.md writes one-by-one.
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.