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    Whipping Boy

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    Force high-reasoning deep research by bridging your agent to the ChatGPT Desktop App via local MCP.

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    Whipping Boy

    Example session with this skill installed

    Run deep research on WebGPU compute pipeline memory barrier synchronization semantics and extract the core sync primitives.

    • Read your context and instructions
    • Compiled the whipping boy

    I have initiated a deep research session via the ChatGPT Desktop bridge with Think mode enabled. The following technical analysis was extracted from the high-reasoning session.

    WebGPU Memory Barrier Synchronization Analysis

    PrimitiveFunctionScopeUse Case
    storageBarrier()Synchronizes storage buffer accesses.WorkgroupCoordinating writes between threads in the same workgroup.
    textureBarrier()Synchronizes texture storage accesses.WorkgroupEnsuring texture writes are visible to subsequent reads in a compute pass.
    workgroupBarrier()Generic workgroup sync (Storage + Texture).WorkgroupUniversal synchronization within a single workgroup context.
    Pipeline BarrierImplicit sync between commands.Command BufferManaged by the API via writeBuffer or pass transitions to prevent hazards.

    Technical Specifications

    Visibility: Memory writes are not automatically visible to other invocations. Barriers must be explicitly called to ensure coherence within the execution set.

    Execution Ordering: Barriers act as a two-way fence. All memory operations before the barrier must complete before any operations after the barrier begin.

    Scope Limitation: The workgroupBarrier only affects invocations within the same workgroup. It does not provide cross-workgroup synchronization.

    Next steps

    1. Implement storageBarrier() in the compute shader to resolve the current race condition in the prefix sum algorithm.
    2. Review the command encoder pass transitions to ensure implicit barriers are correctly handling cross-buffer dependencies.

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    About this skill

    Your primary AI agent often provides superficial summaries when you need deep technical specifications. This skill forces a rigorous, uncompromising deep-dive by offloading complex queries to the ChatGPT Desktop App's Think mode. It bypasses agent laziness to deliver first-principles analysis and architectural details.

    What it does

    • Enforced Think Mode: Programmatically engages the Think button via UI Automation for maximum reasoning depth.
    • Session Isolation: Spawns clean chat contexts using native shortcuts to prevent prompt contamination.
    • Research Scaffolding: Wraps queries in high-density framing that demands technical specifications and formal definitions.
    • Deterministic Extraction: Monitors UI state transitions to copy responses the moment they finish streaming.
    • Clipboard Management: Restores your original clipboard state immediately after extracting research data.

    How it works

    1. Tool Invocation: The agent calls deep_research_gpt with a high-complexity technical prompt.
    2. Bridge Activation: The local MCP bridge interfaces with the Windows ChatGPT Desktop App to open a fresh session.
    3. Execution: The bridge toggles Think mode and submits the inquiry using system-level UI patterns.
    4. Data Return: The skill waits for the final state, captures the full text, and returns it to your agent's context.

    Frameworks & tools

    This skill utilizes Python, Model Context Protocol (MCP), and Windows UI Automation (UIA). It requires the ChatGPT Desktop App for Windows.

    Why this beats prompting it yourself

    Manual deep research requires constant toggling of modes and managing separate chat windows to avoid context pollution. This skill automates the entire UI interaction loop, ensuring every technical query receives maximum reasoning effort without manual intervention.

    Use cases

    • Architectural Analysis: Extracting complex memory barrier semantics for GPU pipelines.
    • Physics Modeling: Retrieving precise material parameters for motion systems.
    • Formal Verification: Generating mathematical derivations for algorithm validation.
    • Spec Compliance: Cross-referencing implementation details against official technical standards.

    Known limitations

    Requires Windows OS and the official ChatGPT Desktop App. Relies on UI Automation, which may require focus permissions or specific app versions to function correctly.

    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.

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    Python
    Windows

    Listed15 days ago

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