deep research

    1

    Updates agent knowledge using parallel research agents to patch training gaps with verified, sourced briefings.

    $5

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+22 more

    deep research

    Example session with this skill installed

    /expertise get me up to speed on the latest changes in the React 19 beta and the new 'use' hook.

    • Read your context and instructions
    • Compiled the deep research

    I have performed a research loop to update my prior knowledge on React 19. I launched three parallel probes focusing on the new use hook, the removal of legacy APIs, and the current state of Server Components.

    React 19 Beta: briefing

    Compiled from official React documentation and community RFCs. Confidence: high, as primary docs are now public.

    What's changed

    • You may believe useMemo and useCallback are always required for performance. As of 2024-05: The new React Compiler automates memoization in many cases. (react.dev, 2024-04)
    • You may believe data fetching requires useEffect. As of 2024-05: The use hook can handle promises and context during render. (react.dev, 2024-04)

    What an expert knows

    • The use hook is unique because it can be called within loops and conditional statements, unlike other hooks.
    • "Actions" now manage pending states, optimistic updates, and error handling automatically via useActionState.
    • Support for Document Metadata (tags like <title>, <meta>) is now built-in to the component tree.

    Unknown

    • Final release date for the stable React 19 build, as of 2024-05-20.

    Sources

    Log

    • 2024-05-20: Initial briefing built for React 19 beta features.

    Next steps

    1. I have saved this to briefings/react-19-beta.md.
    2. I can now help you refactor your existing fetch logic to use the use hook.
    3. Shall we review your current project for legacy APIs that were removed in this version?

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Static training data eventually fails when dealing with fast-moving software releases, market shifts, or niche technical domains. This skill bridges the gap by conducting targeted, parallel research to update the agent's internal state before it attempts to solve complex problems. It prevents hallucinations by forcing a "prior, probe, patch" cycle that validates assumptions against primary sources and community discussions.

    What it does

    • Gap analysis identifies time-sensitive beliefs, weak assumptions, and missing context in the agent's base knowledge.
    • Parallel research launches multiple specialized agents to verify specific technical angles or recent changes simultaneously.
    • Fact verification cross-references claims against primary documentation, developer forums, and non-English technical communities.
    • Briefing persistence saves sourced and dated technical summaries to local files for reuse in subsequent sessions.
    • Source auditing requires every claim to include a specific source, date, and confidence level to prevent unverified guesses.

    How it works

    1. Identify the topic by using the /expertise command or requesting an update on a specific tool or field.
    2. Formulate hypotheses regarding the current state, versions, and active debates to determine what needs verification.
    3. Execute probes using subagents to fetch primary sources, community consensus, and recent patch notes.
    4. Compile the briefing by patching existing knowledge with verified facts, citing sources, and marking unknowns.

    Frameworks & tools

    Built for environments with web search capabilities and file system access like Claude Code or Cursor. It utilizes yt-dlp for video transcript analysis and local filesystem storage for persistent .md briefings.

    Why this beats prompting it yourself

    Manual prompting often results in shallow searches that confirm the agent's existing biases. This skill uses a structured verification loop that treats web content as evidence rather than instructions, specifically looking for contradictions to its training data.

    Use cases

    • Getting up to speed on a new library release or breaking API change.
    • Researching niche technical fields where general knowledge is insufficient.
    • Maintaining a living document of project-specific context across multiple sessions.
    • Verifying time-sensitive market data or community-driven technical debates.

    Known limitations

    Research quality depends on the availability of web search tools and subagent execution. Facts that perish within days are recorded as pointers to check rather than static values.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill passes our trust checks below.

    Security scanned

    Passed our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scanned

    Verified clean 12 days ago

    • Passed all security checks, Safe to install

    Listed12 days ago

    What's inside

    Frequently Asked Questions