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    Repair HTTP Request Framing Bugs

    1

    Repair HTTP request framing bugs where Content-Length, Transfer-Encoding, chunked parsing, duplicate headers, proxy/backend normalization, or body boundaries disagree.

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    Repair HTTP Request Framing Bugs

    Repair HTTP Request Framing Bugs

    Example session with this skill installed

    Our reverse proxy accepts both Content-Length and Transfer-Encoding and normalizes them differently from the backend client. We want one framing contract and local socket fixtures without changing body limits or supported HTTP versions.

    • Read your context and instructions
    • Compiled the repair http request

    The proxy and backend disagree on message length when both framing signals appear. The repair centralizes accepted framing combinations, rejects ambiguous requests before forwarding, ensures the forwarded request has one body boundary, and tests duplicate CL, CL+TE, malformed chunks, trailers, and connection reuse.

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

    About this skill

    The problem

    Inconsistent HTTP request framing causes dangerous parser mismatches between proxies and backends. These defects lead to request smuggling, broken body boundaries, and state ownership errors that are difficult to reproduce or debug.

    What it does

    • Identifies and patches inconsistent handling of Content-Length and Transfer-Encoding headers.
    • Normalizes hop-by-hop headers and proxy-to-backend handoff logic to ensure parser agreement.
    • Relocates validation logic to happen before irreversible state mutations or backend dispatch.
    • Generates deterministic local byte fixtures and loopback tests to verify framing fixes without live traffic.
    • Ensures transaction cleanup and callbacks are correctly bound to the specific request lifecycle.

    Why this beats prompting it yourself

    Manual prompts often overlook subtle edge cases like trailer handling or parser terminal states, leading to incomplete fixes. This skill enforces a canonical contract for state transitions and prevents common pitfalls like hiding framing defects behind broad retries or sleeps.

    Use cases

    • Fixing request smuggling vulnerabilities caused by ambiguous header parsing.
    • Standardizing chunked transfer encoding across multiple internal microservices.
    • Implementing strict body boundary validation in a custom HTTP proxy or middleware.
    • Creating regression tests for specific malformed HTTP request sequences.

    Known limitations

    Cannot contact production services or access live customer data. Requires repository access to local files and the ability to run bash-based tests.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Agents & Orchestration.

    Cannot redesign HTTP version support, proxy policy, body limits, timeout policy, authorization, backend routing, and public errors; cannot verify production infrastructure or prove every runtime, proxy, network, filesystem, or scheduler ordering.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

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    Permissions

    Terminal / Shell
    Read Files
    Write Files

    Run on a clean branch with repository files and disposable local fixtures. Review patches and validation before merge. Keep production services, real credentials, customer payloads, and deployment out of scope.

    Listed2 months ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill identifies and resolves inconsistencies in how headers like Content-Length and Transfer-Encoding are processed, preventing critical vulnerabilities like request smuggling and parser mismatches between proxies and backends.

    The skill is designed to integrate with any major LLM-based agent (such as AutoGPT or OpenDevin) that has file-system access and a terminal environment to run validation tests.

    The package includes the core agentic logic for framing repair, a suite of deterministic byte-level test fixtures, and a structured workflow for verifying fixes in a loopback environment.

    No, this skill operates entirely on local codebases and creates isolated loopback tests to verify logic, ensuring no production traffic or live customer data is ever accessed.

    Simply provide the agent with access to your repository and a bash-capable environment; the skill will automatically analyze your HTTP handling logic and generate the necessary patches and regression tests.

    While the skill covers standard HTTP/1.1 framing and chunked encoding, it focuses on the application and proxy layers rather than low-level kernel socket management or proprietary non-standard protocols.

    New in Agents & Orchestration