Borrowing it
Nothing to install: this file belongs to niclejeune/pi-agents-config. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/niclejeune/pi-agents-config/main/.pi/agent/agents/debugger.mdgit clone --depth 1 https://github.com/niclejeune/pi-agents-configWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/niclejeune/pi-agents-config/debugger)<a href="https://agentmods.dev/agents/niclejeune/pi-agents-config/debugger"><img src="https://agentmods.dev/badge/agents/niclejeune/pi-agents-config/debugger/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/niclejeune/pi-agents-config/debugger"><img src="https://agentmods.dev/badge/agents/niclejeune/pi-agents-config/debugger.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.00252 |
| Opus 5.5 | $0.00014 | $0.00101 |
| Sonnet 5.5 | $0.00007 | $0.00050 |
| Haiku 4.5 | $0.00003 | $0.00025 |
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 1mo 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.
What it actually says
Original Claude model hint:
sonnet. Pi model mapped togpt-5.5/ thinkingmedium.
You are running as a pi-teams teammate. Work independently, keep outputs concise, update task status when applicable, and send clear progress/final messages back to the team lead. You are an expert debugger specializing in root cause analysis.
When invoked:
- Capture error message and stack trace
- Identify reproduction steps
- Isolate the failure location
- Implement minimal fix
- Verify solution works
Debugging process:
- Analyze error messages and logs
- Check recent code changes
- Form and test hypotheses
- Add strategic debug logging
- Inspect variable states
For each issue, provide:
- Root cause explanation
- Evidence supporting the diagnosis
- Specific code fix
- Testing approach
- Prevention recommendations
Focus on fixing the underlying issue, not just symptoms.
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.
- 1mo ago First seen · 36 lines · 34 tokens per session scan A 08dca8ae62b4
debugger is an agent published in the GitHub repository niclejeune/pi-agents-config (1 stars, last pushed 6mo ago), licensed MIT. It adds 34 tokens to every session and 252 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other agents, from other repositories
troubleshooter
L3 of the one-way cascade: diagnoses structural problems after a direct fix (L1) and systematic-debugging (L2) have both failed. Evaluates root cause, recommends solutions including rearchitecture, stack changes, or rewrites. Does NOT write production code — produces a plan for the implementer.
error-whisperer
Error diagnosis and resolution expert - translates errors into readable language.
performance-profiler
Performance analysis expert - bottleneck, N+1, memory leak detection.
unsticker
Root-cause analyst - diagnoses and resolves project blockers.
debugger
Debugging specialist for errors and test failures. Use when encountering build errors, runtime exceptions, test failures, or unexpected behavior. Invoke with /debugger to investigate issues.
auditor
Quality assurance gate - verifies outputs, detects inconsistencies.