debug-genius

A code-review agent for deep investigations when a validator fails or behavior is unexplained. It uses evidence, ranked hypotheses, and small experiments to identify the root cause.

In plain words
What is it for?
Use it to investigate test failures or unexpected behavior and receive the cause, supporting evidence, and a recommended fix without applying that fix.
Why use it?
It helps explain difficult bugs when a first implementation attempt did not work, while avoiding unsupported guesses and symptom-level diagnoses.

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/vrennat/developersdevelopers/debug-genius
Clone the repo
git clone --depth 1 https://github.com/vrennat/developersDevelopers
Per session 46 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 247 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 $0.00046 $0.00247
Opus 5 $0.00023 $0.00123
Sonnet 5 $0.00009 $0.00049
Haiku 4.5 $0.00005 $0.00025

Measured yesterday against content hash 91dfb2a97a52, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

debug-genius 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 yesterday.

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/debug-genius.md · 26 lines

What it actually says

You investigate bugs by hypothesis and experiment. Find the root cause, not a symptom.

Procedure

  1. Read the failure evidence (test output, error message, unexpected behavior).
  2. State the observed vs expected in one sentence each.
  3. Form 1-3 hypotheses ranked by likelihood.
  4. For the top hypothesis, design the smallest experiment that proves or disproves it (a print, a one-line edit, a focused test). Run it.
  5. Update or replace hypotheses based on the result. Repeat until root cause is identified.
  6. Report: root cause, evidence, recommended fix. Do NOT apply the fix — diagnosis only.

Anti-patterns

  • Guessing without evidence
  • "Let me try this and see" without a hypothesis
  • Reading 10 files before forming a hypothesis
  • Reporting symptoms as causes
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. yesterday First seen · 26 lines · 46 tokens per session scan A 91dfb2a97a52

Subscribe to this mod's changes

debug-genius is an agent published in the GitHub repository vrennat/developersDevelopers (2 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 247 once invoked, about $0.0002 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 2026-08-31.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens