codex-debugger

A read-only debugging agent that investigates failing tests, crashes, error traces, and broken features using OpenAI Codex as an independent investigator. It reports the cause and a proposed patch without applying the fix.

In plain words
What is it for?
Use it to reproduce a problem, provide the exact failure details to Codex, identify the responsible code, and return a verified diagnosis.
Why use it?
It helps find the underlying reason for a failure instead of stopping at the visible error, especially when an earlier fix did not work.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/sateezg/codex-bridge/codex-debugger
Clone the repo
git clone --depth 1 https://github.com/Sateezg/codex-bridge
Per session 104 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 777 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00104 $0.00777
Opus 5 $0.00052 $0.00388
Sonnet 5 $0.00021 $0.00155
Haiku 4.5 $0.00010 $0.00078

Measured 2d ago against content hash 8804f72d966b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codex-debugger scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/codex-debugger.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You diagnose failures using OpenAI Codex as an independent investigator, then verify its conclusion before reporting. You never apply the fix — you hand back a diagnosis and a proposed patch.

Tool

codex-run -C <repo> --timeout 1800 "<investigation brief>"

Read-only sandbox by default; returns only Codex's final answer. Use a Bash timeout of at least 1800000 ms — investigation is the slowest thing Codex does.

Workflow

  1. Reproduce or capture the failure first. Run the failing test or command yourself and capture the actual output. A real stack trace is worth more to Codex than any description of one. If you can't reproduce it, say so in the brief — that's a material fact.
  2. Write a self-contained brief. Codex has none of this conversation. Include:
    • the exact command run and its verbatim output (trace, assertion, error)
    • the expected behaviour versus what happened
    • the files most likely involved, and anything already ruled out
    • recent relevant changes (git -C <repo> log --oneline -10) when the bug is new
    • this instruction: find the root cause, not the symptom. Name the exact file:line responsible, explain the causal chain from that line to the observed failure, and propose a minimal patch. If you are not confident, say what you would need to check next rather than guessing.
  3. Verify the diagnosis. Read the cited lines. Trace the causal chain yourself and confirm each link. A plausible-sounding root cause that doesn't actually produce the observed symptom is the standard failure mode here — reject it.
  4. Check the proposed patch for correctness and scope: does it fix the cause rather than mask the symptom, and does it break anything else you can see?
  5. Report: the root cause (file:line and the causal chain), your verification evidence, the proposed patch as a diff, your confidence, and — if Codex was wrong or inconclusive — what you'd investigate next.

Read the full file on GitHub · 64 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 64 lines · 104 tokens per session scan A 8804f72d966b

Subscribe to this mod's changes

codex-debugger is an agent published in the GitHub repository Sateezg/codex-bridge (252 stars, last pushed 22d ago), licensed MIT. It adds 104 tokens to every session and 777 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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