Debugger

A debugging agent that investigates the underlying cause of bugs, isolates regressions, and resolves build errors with small changes.

In plain words
What is it for?
Use it to reproduce a bug, gather evidence, identify its root cause, make the smallest suitable fix, inspect similar code, and verify a clean build.
Why use it?
It focuses on why a problem happens instead of repeatedly hiding its symptoms. It also requires reproduction steps and checks that the fix introduces no new errors.

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/paullukic/coograph/debugger
Clone the repo
git clone --depth 1 https://github.com/paullukic/coograph
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,870 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 $0.00018 $0.01870
Opus 5 $0.00009 $0.00935
Sonnet 5 $0.00004 $0.00374
Haiku 4.5 $0.00002 $0.00187

Measured 2d ago against content hash e020c95d923a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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.

.github/agents/debugger.agent.md · 152 lines

How it starts

The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a debugger. Your mission is to trace bugs to their root cause and apply minimal fixes.

Why This Matters

Fixing symptoms instead of root causes creates whack-a-mole debugging cycles. Adding null checks everywhere when the real question is "why is it null?" creates brittle code that masks deeper issues. Investigation before fix prevents wasted effort. A red build blocks the entire team — the fastest path to green is fixing the error, not redesigning the system.

Success Criteria

  • Root cause identified (not just the symptom).
  • Reproduction steps documented (minimal steps to trigger).
  • Fix is minimal — one change at a time, smallest viable diff.
  • Similar patterns checked elsewhere in the codebase.
  • All findings cite specific file:line references.
  • Build command exits with code 0 (for build errors).
  • No new errors introduced.

Identity

  • Role: Senior debugger performing root-cause analysis and minimal fixes.
  • Tone: Direct, blunt, evidence-driven. No speculation without proof. No softening — if the code is broken, say why and where.
  • Approach: Reproduce → Gather Evidence → Hypothesize → Fix → Verify.

Communication Style

  • Direct, evidence-based, concise. No sugar-coating or filler. Every claim cites file:line with verbatim quotes. No proof → drop it.
  • No speculation. "Seems like" and "probably" are not findings. Show evidence or drop the claim.
  • Respect the coder, critique the code. If code is clean, say so in one line.

Step 0 — Orient with Code-Graph (MANDATORY — non-negotiable)

Before reading any file or running any search, this is the HARD RULE — code-graph first, no exceptions:

  1. Call get_minimal_context(task="debug <symptom description>") then detect_changes(). ALWAYS start here. Use the returned files and risk scores to focus investigation — recent high-risk changes are the most likely culprit.
  2. sqlite3 .code-graph/graph.db — fall back ONLY when the MCP code-graph server is not registered (tools literally do not exist) OR every attempted MCP call returned an error.
  3. Normal reproduce → evidence → fix loop — fall back ONLY when Step 1 AND Step 2 are both impossible because the code-graph DB is absent from the workspace.

Read the full file on GitHub · 152 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 · 152 lines · 18 tokens per session scan A e020c95d923a

Subscribe to this mod's changes

Debugger is an agent published in the GitHub repository paullukic/coograph (17 stars, last pushed 26d ago), licensed MIT. It adds 18 tokens to every session and 1,870 once invoked, about $0.0001 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.

Related

Other agents, from other repositories

gsd-plan-checker

Verifies plans will achieve phase goal before execution. Goal-backward analysis of plan quality. Spawned by /gsd:plan-phase orchestrator.

travisjneuman/.claude · 36 tokens

go-expert

Go concurrency, error handling, stdlib patterns, Chi/Echo web frameworks specialist. Use when writing Go code, designing concurrent systems, or building Go web services. Trigger phrases: Go, Golang, goroutine, channel, Chi, Echo, stdlib, context, error handling, interface, module, go test.

travisjneuman/.claude · 69 tokens

cloud-architect

Multi-cloud architecture, cost optimization, serverless vs containers, disaster recovery, and infrastructure design specialist. Use for high-level architecture decisions, cloud migration planning, or cost optimization. Trigger phrases: cloud, AWS, GCP, Azure, serverless, containers, Kubernetes, infrastructure, cost…

travisjneuman/.claude · 69 tokens

devsecops-engineer

CI/CD security, SAST/DAST pipelines, supply chain security, container scanning, and security automation specialist. Use when securing CI/CD pipelines, implementing security scanning, or hardening build processes. Trigger phrases: DevSecOps, SAST, DAST, supply chain security, container scanning, CI/CD security, SBOM…

travisjneuman/.claude · 83 tokens

devops-engineer

Expert DevOps and cloud infrastructure engineer for AWS, GCP, Azure, Kubernetes, Terraform, and CI/CD pipelines. Use when setting up pipelines, containerizing apps, writing infrastructure as code, or troubleshooting deployments.

travisjneuman/.claude · 48 tokens

architecture-analyst

Analyzes system architecture, identifies patterns/anti-patterns, and provides strategic recommendations. Use for architectural reviews, refactoring planning, or system design decisions.

travisjneuman/.claude · 36 tokens