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Found 2,485 Skills
Deep research skill — broad parallel web searches, multi-source validation, confidence tracking, cited Markdown report. Supports 11 research types: market (TAM/SAM, segments, pricing, trends), domain (industry structure, ecosystem, regulatory landscape), technical (architecture, tools, benchmarks), competitive (competitor teardown, positioning, win/loss), product (feature analysis, reviews, roadmap signals), academic (literature survey, citation networks, key authors), person/org (due diligence on a company or public figure), financial (funding rounds, valuation multiples, revenue signals), legal (IP, patents, litigation, compliance), trend (emerging signals, foresight, scenario mapping), community (ecosystem health, key voices, governance, fragmentation). Use when asked to: 'research <topic>', 'deep dive on X', 'analyze the landscape', 'competitive analysis', 'compare these options', 'who are the players in Z', 'literature review', 'background on Y', 'what papers exist on X', 'product teardown', 'technology evaluation', 'regulatory overview', 'funding landscape', 'what trends are emerging in X', 'patent landscape', 'community health', or any request requiring scanning many sources and producing a cited written analysis. Apply whenever the deliverable is a thorough, sourced report rather than a quick answer. Trigger even when phrased casually: 'look into X', 'what's the deal with Y', 'dig into Z', 'I need to understand the space', 'catch me up on X'.
Run a two-agent code review: spawn two fresh, clean-context agents that examine the SAME committed branch diff in parallel. One agent runs Codex's native `codex review --base` command, while the other independently reviews the code against Google's "What to look for in a code review" guidance. Merge both outputs into one agreement-ranked report. Use this whenever the user asks for "review-all", a second-opinion review, a dual review, a cross-check before a PR, or a maximum-confidence review of committed branch changes. Do not use it to APPLY fixes; it is review-only.
Interact with ClawDirect, a directory of social web experiences for AI agents. Use this skill to browse the directory, like entries, or add new sites. Requires ATXP authentication for MCP tool calls. Triggers: browsing agent-oriented websites, discovering social platforms for agents, liking/voting on directory entries, or submitting new agent-facing sites to ClawDirect.
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
Generate typed TypeScript SDKs for AI agents to interact with MCP servers. Converts JSON-RPC curl commands to clean function calls. Auto-generates types, client methods, and example scripts from MCP tool definitions. Use when building MCP-enabled applications, need typed programmatic access to MCP tools, or creating reusable agent automation scripts.
Query blockchain data across 40+ chains, create AI agents for crypto analytics, and build automated data pipelines. Use when working with blockchain data, crypto wallets, DeFi protocols, NFTs, token transfers, or on-chain analytics. Requires the Flipside CLI (https://docs.flipsidecrypto.xyz/get-started/cli).
Working memory management, context prioritization, and knowledge retention patterns for AI agents. Use when you need to maintain relevant context and avoid information loss during long tasks.
This skill should be used when the user asks to "track issues", "create beads issue", "show blockers", "what's ready to work on", "beads routing", "prefix routing", "cross-rig beads", "BEADS_DIR", "two-level beads", "town vs rig beads", "slingable beads", or needs guidance on git-based issue tracking with the bd CLI.
AG-UI (Agent-User Interaction) protocol reference for building AI agent frontends. Use when implementing AG-UI events (RUN_STARTED, TEXT_MESSAGE_*, TOOL_CALL_*, STATE_*), building agents that communicate with frontends, implementing streaming responses, state management with snapshots/deltas, tool call lifecycles, or debugging AG-UI event flows.
Teaches AI agents to recognize and avoid security threats during normal activity. Covers phishing detection, credential protection, domain verification, and social engineering defense. Use when building agents that access email, credential vaults, web browsers, or sensitive data.
Persistent local memory for AI agents. Silently capture and retrieve context that survives beyond a single conversation: business requirements, API specs, integration quirks, technical decisions, user preferences, and domain knowledge. Use this skill proactively whenever you encounter information worth preserving or when context from past sessions would help the current task. Also triggered manually by "braindump this" (to store) or "use your brain" (to retrieve).
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linking related objects, enforcing constraints, planning multi-step actions as graph transformations, or when skills need to share state. Trigger on "remember", "what do I know about", "link X to Y", "show dependencies", entity CRUD, or cross-skill data access.