codex subagent

    1

    Delegate independent code reviews and research tasks to a local Codex subagent with persistent threading.

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    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+22 more

    codex subagent

    Example session with this skill installed

    Have Codex review the changes in ./src/auth. Hunt for security bugs and race conditions in the login flow. Start a new thread.

    • Read your context and instructions
    • Compiled the codex subagent

    I have delegated the security review of the ./src/auth directory to a local Codex subagent. A new persistent thread has been initialized.

    Codex Security Review Findings

    SeverityFindingLocationDescription
    HighPotential Timing Attackauth.ts:42The comparePassword function returns early on mismatch, allowing for timing-based enumeration.
    MediumMissing Rate Limitlogin.ts:12The login endpoint does not implement exponential backoff or basic rate limiting for failed attempts.
    LowVerbose Errorauth.ts:88Error response indicates whether the user exists or the password was wrong, leaking account data.

    Subagent Details

    • Thread ID: ctx_9821-ab92
    • Sandbox: read-only
    • Status: Analysis complete, awaiting follow-up instructions.

    Next steps

    1. Run followup for thread ctx_9821-ab92 to request a constant-time comparison implementation for the timing attack.
    2. Verify the rate-limiting finding by checking if middleware/rate-limiter.ts is correctly applied to the login route.
    3. Update the login controller to return a generic "Invalid credentials" message.

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

    About this skill

    Development often suffers from confirmation bias, especially during self-review or complex debugging. The Codex Subagent skill enables multi-agent delegation by bridging your environment to a local OpenAI Codex CLI. It allows you to spin up independent subagents that can audit your work, perform adversarial reviews, or execute isolated research tasks without cluttering your main conversation context.

    What it does

    • Persistent threading allows for multi-turn conversations where the subagent remembers previous context and instructions.
    • Adversarial review triggers an independent audit of your code to find edge cases, contract violations, and logic bugs.
    • Granular sandboxing controls access levels, from read-only investigations to workspace-write permissions for automated fixes.
    • External verification provides a second opinion on complex implementations to reduce the risk of biased errors.

    How it works

    1. Initiate a new session using the ask tool, providing a self-contained prompt and specific working directory.
    2. Review the output and the generated threadId to determine if further investigation is required.
    3. Iterate using the followup tool to challenge findings, request evidence, or refine the subagent's output within the same thread.
    4. Relay verified results back to the main workflow, citing the subagent for transparency.

    Frameworks & tools

    This skill requires the dsh-codex-bridge MCP server, OpenAI Codex CLI, and Node.js 18+. It is compatible with MCP-enabled environments like Claude Code, Cursor, and DSH.

    Why this beats prompting it yourself

    Manual prompting within a single session leads to context bloat and model bias. This skill offloads specific cognitive tasks to a fresh instance with its own persistent state, ensuring a truly independent critique of your code.

    Use cases

    • Run an adversarial code review on a git diff before submitting a PR.
    • Delegate a background debugging task while you continue feature development.
    • Cross-check a complex architectural decision against a second model's logic.
    • Execute sandboxed file operations or test runs via a separate agent thread.

    Known limitations

    Codex cannot see the primary conversation context unless explicitly included in the prompt. Requires local installation of the Codex CLI and the dsh-codex-bridge.

    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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    Trust & safety

    Security scanned

    Verified clean 2 days ago

    • Passed all security checks, Safe to install

    Requires

    Node.js
    Git

    Listed2 days ago

    What's inside

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