Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Agent workflows
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Read metadata, DOM, screenshots, and structured page payloads from an attached Chrome or Chromium tab through the local Agent Browser Relay extension. Use when Codex needs relay preflight or troubleshooting, popup attach guidance, lease-scoped concurrent tab reads, or new background tab creation through the relay without direct browser automation.
MUST USE when user wants to research/search/look up/find anything on the internet—e.g. “research this topic”, “do a deep dive on X”, “search the web for X”, “see what people say about X”, “look this up”. Also MUST USE when user mentions any platform or shares any URL/link: Twitter/X, Reddit, Facebook, Instagram, YouTube, GitHub, Bilibili, XiaoHongShu, Xiaoyuzhou Podcast, LinkedIn/jobs/recruiting, V2EX, Xueqiu (stocks), RSS. 15 platforms, multi-backend routing (OpenCLI / per-platform CLIs / APIs). Zero config for 6 channels. Run `agent-reach doctor --json` to see which backend serves each platform right now. NOT for: writing reports/analysis/translation (this skill only FETCHES internet content); posting/commenting/liking (write operations); platforms that already have a dedicated skill installed (prefer that skill).
Use to design, understand, tune, or audit a non-trivial model workflow, including framework-undecided designs, partial implementations, and production reviews: model-node responsibilities, input/output completeness, data-flow correctness or redundancy, model-versus-Host/workflow ownership, topology, evidence, lifecycle, concurrency, or observed execution effects. The user need not say Prompt review or name Agently. Use agently-request for one request family and agently-triggerflow for already-decided executable orchestration details.
Use when past-change rationale matters (refactoring unfamiliar code, revert or hotfix analysis, issue-linked commit archaeology, session authors git changes with human-authored messages) — injects the published ChDR index (docs/adlc/memory/chdr/chdr.md, legacy .adlc/memory/chdr.md fallback) as session context; pairs history mining (/change-init) with in-session capture suggested via /change-specify (never writes drafts itself), clarified via /change-clarify; invoked from team-boot's Class Boots catalog
Access OpenAI Codex CLI conversation history to continue work started in Codex, or to find a past Codex chat by topic or keyword. Use when the user says "codex history", "continue from codex", "what was I doing in codex", "pick up from codex", "codex session", "find the codex chat about X", or wants to resume or locate a task that was started in Codex CLI.
Automated code review workflow using OpenAI Codex CLI. Implements iterative fix-and-review cycles until code passes validation or reaches the iteration limit. Use when building features requiring automated code validation, security checks, or quality assurance through Codex CLI.
Build Model Context Protocol (MCP) servers in C#/.NET against the current ModelContextProtocol 2.x NuGet packages. Helps with cases the model gets wrong without guidance — stale versions (0.x preview or 1.x-era defaults), the v2 stateless-by-default HTTP flip, the 2026-07-28 spec deprecations (roots/sampling/logging), MCP Apps and Tasks extension packages, elicitation URL mode, per-session HTTP wiring, OAuth and reverse-proxy deploy specifics, and debugging MapMcp / STDIO / Streamable-HTTP errors. Also covers STDIO and Streamable HTTP transports (SSE is deprecated), tools, prompts, resources, completions, and a basic .NET MCP client. Trigger when the user says or implies any .NET MCP server work: ModelContextProtocol, McpServerTool, MapMcp, WithStdioServerTransport, “MCP server in C#”, “MCP tool in dotnet”, “expose this as MCP”, or names a primitive (prompt/resource/elicitation/MCP App) in a .NET context. Skip for MCP work in other languages.
Domain navigator for Figma, design-to-code, design tokens, and official platform skill suites. Routes to the right skill for working between design tools and code, managing design systems, or using official platform skills (Anthropic, Vercel, Expo, Software Mansion, Callstack)
A WorkBuddy/OpenClaw adaptation of gstack. Derived from gstack (Y Combinator Garry Tan), it is optimized for AI assistant platforms such as WorkBuddy/OpenClaw. Includes 15 specialized tools covering the complete development workflow from product ideation to code release.
Troubleshoot and operate OpenClaw browser on local or remote gateways. Use when Codex needs to enable the bundled browser plugin, resolve `pairing required` or device approval errors, choose between the managed `openclaw` profile and the attached `user` profile, handle Linux headless or Chrome CDP startup failures, or prove browser control with `profiles`, `start`, `open`, `snapshot`, and `screenshot`.
Large collection of specialist agent skills coordinated by an orchestrator, with a design suite: Vision (creative direction, design systems), Muse (design tokens, theming, dark mode), Frame (Figma-to-code context via MCP), Pixel (pixel-accurate HTML/CSS from mockups), Echo (simulated persona UX validation), Prose (microcopy and UX writing), and Ink (SVG icons and illustrations). The catalogue installs only these design skills.
Run GitHub's Spec-Driven Development (SDD) workflow via the `specify` CLI — install spec-kit, initialize a project for one of 30+ AI coding agents (Claude Code, Copilot, Gemini, Cursor, Codex, Qwen, opencode, Kiro, etc.), and drive the constitution → specify → plan → tasks → implement command pipeline. Use when the user wants to bootstrap a Spec-Driven Development project, install `specify-cli`, generate executable specs before code, or invoke the `/speckit.*` slash commands (`/speckit.constitution`, `/speckit.specify`, `/speckit.plan`, `/speckit.tasks`, `/speckit.implement`, `/speckit.clarify`, `/speckit.analyze`, `/speckit.checklist`). Triggers on: spec-kit, speckit, specify, specify init, spec-driven, spec driven development, SDD, /speckit, executable spec.
Lightweight standalone design spec for AI coding agents: codebase scan → bounded clarify pass (3–5 questions, not a grill) → reviewed design doc written to docs/plans/ → independent scored review → stop. No task board, no build. Use when you want a spec to discuss, hand off, or review before committing to implementation. Chains into absolute-work when ready to build. Triggers on "absolute spec", "write a spec", "spec out this feature", "draft a design doc", "I want a spec to hand off / review, don't build it yet".
Install and configure `agent-browser` on a Windows machine with WSL2 after a browser path is already working. Use when a user wants the `agent-browser` CLI, its downloaded runtime, the `vercel-labs/agent-browser` repository, or an `agent-browser` attachment to a Windows host browser bridge from WSL2.
Check an installed skills-for-fabric plugin bundle or git clone for updates, show the matching changelog, and provide host-appropriate update guidance. Use when the user wants to: (1) check for skill updates, (2) see what changed, or (3) verify the installed version. Triggers: “check for updates”, “am I up to date”, “what version”, “update skills”, “show changelog”.
Explain or reason about foundational context engineering concepts: what context is, the anatomy of a context window, attention mechanics, the U-shaped attention curve, why context quality matters more than quantity, and the mental models needed to interpret context-engineering decisions. Use for conceptual explanation, onboarding, and background reading. Route operational work to context-degradation for attention failures and context-optimization for token-efficiency work
Multi-agent investigation for stubborn bugs. Use when: going in circles debugging, need to investigate browser/API interactions, complex bugs resisting normal debugging, or when symptoms don't match expectations. Launches parallel agents with different perspectives and uses Chrome tools for evidence gathering
Reasoning protocol distilled from Claude Fable 5 — Floor check, multi-hypothesis diagnosis, adversarial self-review, Constraint Loop for hard output constraints. Use when the user says "fable5", "bật thinking mode", "reason like fable 5", or invokes /fable5. Once invoked it stays active for the rest of the session (toggle off with "stop fable5" / "normal mode")
Discover and route Jinkō QSP and mechanistic-modeling requests to the public Jinkō skill that owns the work. Use when the user is starting a Jinkō session, asks what capability or skill to use, describes a multi-area modeling request, or has not yet identified the relevant jinko-* or jinko-task-* skill. This skill does not make scientific decisions, plan workflows, execute SDK calls, or decide that a task step is complete.
How to connect AI agents to MariaDB using the Model Context Protocol (MCP). Use when setting up MCP with MariaDB, connecting Claude Code, Cursor, or other AI tools to a MariaDB database, enabling natural language database queries, or building AI applications that need live database access. The MariaDB MCP Server lets agents query schemas, run read-only SQL, and perform semantic search against MariaDB.
Creative director and orchestrator for Pawbytes Creative Suites. Use when the user needs creative direction, campaign planning, brand setup, or help choosing the right creative specialist or workflow. Triggers: “Aria,” “creative direction,” “campaign planning,” “brand setup,” “which creative agent should I use,” “creative suite”.
Signals scout for PostHog MCP tool calls. Watches `$mcp_tool_call` telemetry for tools that need improvement — broad-reach failure rates, retry hammering, slow or context-bloating responses — grouped by owning product category, each with a fix suggestion.
Propagate ONE validated learning about Claude Code behavior from this session into the project's CLAUDE.md — the MAIN-AGENT memory Claude loads every session, not agent or skill files. Extract the smallest useful workflow/scope/session rule, place it in the correct section (Workflow Rules / Session Management / Scope Control / Behavioral Patterns), and preserve the surrounding structure. User-only maintenance workflow that mutates durable project memory: it grounds the rule in what THIS session revealed, never invents, checks for duplicates, and confirms wording and placement before writing. Use to make a Claude-behavior rule persist into future sessions.
Configure WayAI hubs, agents, tools, channels, skills, states, evals, automations, and analytics, plus the Data surface (bases, record types, records, relationships, files, toolsets), and live AI voice calls. Use when: creating or editing a hub or hub config; adding/configuring agents, tools, channels, connections, teams, kanban, states, skills, eval scenarios or journeys, automations (scheduled or event-triggered sends and agent runs, webhook-started tasks), voice calls; running analytics or evals; annotating conversation outcomes; reviewing or editing workspace YAML (hub.yaml, agents/*.yaml, base.yaml, record-types/*.yaml) or agent instruction Markdown; designing a base schema, upserting or querying records, linking records with relationships, storing versioned files or attachments, wiring inbound webhooks, triggers or external sources, building MCP toolsets and Actions, scoping base API tokens, or seeding eval fixtures; using the wayai CLI (push, pull, publish, send-message, conversations, sync-skills, create-credential, update-credential, analytics, analytics sql, run-eval, eval capture, eval call, evals sql, org, init, communities, bases, records, record-types, relationships, files, toolsets, actions, triggers, inbound-webhooks, seed); managing an organization's communities (list, join link, stats, the access list of an invite-only community; settings including who may join, rules, rooms and courses as code); analyzing LLM token/cost spend per message, model, agent, or credential; interpreting WayAI platform terminology (pilot/copilot, preview/production, kanban statuses, AI modes, agent roles, journeys, base, record type, promotion, external_id); or answering how people use the app: end users (agents, tasks, files, the mobile and desktop apps) and support teams (the inbox, claim, transfer, close, the board, Copilot suggestions, consults).
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to “open a website”, “fill out a form”, “click a button”, “take a screenshot”, “scrape data from a page”, “test this web app”, “login to a site”, “automate browser actions”, or any task requiring programmatic web interaction.
How to author, edit, and adapt PostHog Signals scouts—the scheduled agents that scan a project and emit findings into the Signals inbox. Use when a user wants to customize a canonical scout for their own setup (narrow its scope, retune its thresholds, add disqualifiers), tweak a scout's schedule or dry-run posture, or write a brand-new scout from scratch for a specific use case (a custom event, a product surface no canonical scout covers). Covers the scout SKILL.md anatomy, the emit contract, the dedupe + scratchpad-memory conventions, the per-team skills-store path vs the canonical in-repo path, and the emit-and-inspect test loop (with dry-run as an optional safety net). Trigger on “write/edit/customize a signals scout,” “new scout for X,” “tune my scout schedule,” “make a scout that watches <event>.”
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.