Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

Estimate total token usage and cost across conversation history, system prompts, and active rules. Use when the user asks how much context or how many tokens are in use, to audit context size, or to estimate session cost.

Create, maintain, and run evidence-based benchmarks for AI agents. Use when setting up testing infrastructure, writing new test scenarios, or evaluating agent performance.

Guide for creating effective Subagents (custom agent definitions). Use when users want to create a new subagent, set up task-specific agents, configure code reviewers, debuggers, or domain-specific assistants. Works across IDEs (Cursor, OpenCode).

Guide for creating effective Agent Skills (SKILL.md packages). Use when users want to create a new skill, write a skill, author a SKILL.md, or ask about skill structure, best practices, or skill file format. Works across IDEs (Cursor, Claude Code, OpenCode).

Guide for creating persistent AI rules (coding standards, project conventions, file-specific patterns). Use when users want to create a rule, add coding standards, set up project conventions, configure file-specific patterns, or ask about rules placement. Works across IDEs (Cursor, Claude Code, OpenCode).

Creation and configuration of event hooks/plugins to manage agent behavior, command filtering, auditing, and automation. Works across IDEs (Cursor, Claude Code, OpenCode). Use when you need to: (1) Create a new hook (e.g., for formatting or security checks), (2) Configure hooks/plugins, (3) Implement logic for blocking or modifying agent actions via scripts.

Guide for creating effective flowai commands. This skill should be used when users want to create a new command (or update an existing command) that extends flowai's capabilities with specialized knowledge, workflows, or tool integrations. Works across IDEs (Cursor, Claude Code, OpenCode).

Manage Deno Deploy cloud services using both `deno deploy` and `deployctl`. Use this skill for deploying projects, managing cloud environments (Build/Dev/Prod contexts), monitoring logs, and troubleshooting deployment issues (like private npm dependencies).

Manage all Deno capabilities via CLI (run, test, fmt, lint, task, add, etc.). Use this skill when you need to execute Deno commands, manage dependencies, run tests, or handle local development workflows.

Recommend which LLM model to use for a task. Use when asked "which model / best LLM for X", "pick a model for this task", or for a model shortlist ranked by live leaderboard evidence (coding, reasoning, agentic, tool-use, price, speed). Live-fetches public leaderboards and ranks models with per-axis rationale and citations.

Delegate a task to another AI IDE's CLI (codex / claude / opencode / cursor-agent) through an isolated-context subagent. Triggers on "delegate to <ide>", "have <ide> do <task>", "execute <task> in <ide>", "offload to <ide>". For one-shot relay or fan-out comparison use `ai-ide-runner` instead.

Run prompts in Claude Code, OpenCode, Cursor, or Codex CLIs from the current session — pick one IDE, fan out across several, or compare models. You are a courier that relays the other runtime's stdout verbatim, do not synthesise your own answer. Use on "run in <ide>", "compare <ide> vs <ide>", "try on <model>", "which IDE handles X better", "run across models".

高效 Agent 间通信协议，使用向量编码减少 7-10x Token 消耗。当需要 Agent 协作、批量消息传输或节省 Token 时使用 (Efficient Agent-to-Agent communication protocol using vector encoding to reduce token consumption by 7-10x. Use when Agent collaboration, batch message transfer, or token saving is needed)

Build a fast, runnable simulation of a system's safety rules and attack it with hostile inputs to find where it fails BEFORE production — without starting any service. Use this whenever the user wants to "simulate the system", "verify without running it", stress-test invariants, find edge cases / outliers, prove a pipeline or workflow is safe, model a system's rules, or harden code against weird/malicious input. Also use proactively after building any system with safety or correctness invariants (auth, redaction, access control, validation, state machines, data pipelines, payment/ledger logic, agent tool contracts) — the happy-path tests almost never cover the hostile path, and this finds the gap cheaply. Triggers on: "simulate", "model the rules", "edge cases", "stress test", "what could break", "is this safe", "adversarial test", "find outliers".

File system watcher and AST parser. Detects changes in the watched repository, extracts AST structure using tree-sitter, and emits structured ChangeEvents for the Architect to process.

Multi-threaded conversation memory organized by topic instead of by date. Enables seamless context switching, compaction resilience, and sub-agent tracking — all file-based, no code changes to OpenClaw. Use when you want your agent to maintain separate conversation threads per project/topic, survive context compaction without losing the thread, track sub-agent spawns with model/task/duration, and output a structured conversation-map.json for visualization clients.

Build AI agents with Honi (honidev) on Cloudflare Workers. Use when creating agents with tools, persistent memory, MCP servers, or multi-agent pipelines. Covers createAgent API, tool() helper, all memory tiers (working/episodic/semantic/graph), multi-agent routing, MCP auth, and all supported model providers.

Semantic chunker, embedding engine, and ChromaDB store. Consumes ChangeEvents from the Scout, chunks files at function/class boundaries, generates embeddings, and manages the vector store.

Operating manual for Lens — a reactive data canvas. Drive the pipeline by editing query.json (a node graph of source/SQL/semantic/chart nodes).