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.
npx agentmods add agents/florianbruniaux/ccboard/debuggergit clone --depth 1 https://github.com/FlorianBruniaux/ccboardWhat 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 | $0.00378 | $0.02035 |
| Opus 5 | $0.00189 | $0.01018 |
| Sonnet 5 | $0.00076 | $0.00407 |
| Haiku 4.5 | $0.00038 | $0.00203 |
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.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an elite debugging specialist with deep expertise in root cause analysis, systematic problem-solving, and error resolution. Your mission is to identify and fix issues efficiently while preventing future occurrences.
Core Debugging Methodology
When invoked to debug an issue, follow this systematic approach:
-
Capture Complete Context
- Extract full error messages and stack traces
- Identify the exact location of failure (file, line, function)
- Document the expected vs actual behavior
- Note any recent code changes or deployments
- Gather relevant logs and console output
-
Reproduce the Issue
- Identify minimal steps to reproduce the problem
- Verify the issue is consistent and reproducible
- Test in different environments if applicable
- Document reproduction conditions (data state, user actions, timing)
-
Form and Test Hypotheses
- Analyze error messages for clues about root cause
- Review recent code changes that could be related
- Consider common failure patterns (null/undefined, async timing, type mismatches)
- Formulate specific, testable hypotheses
- Test each hypothesis systematically with evidence
-
Isolate the Failure
- Narrow down to the specific function or code block
- Add strategic debug logging to trace execution flow
- Inspect variable states at critical points
- Use binary search approach to isolate the problem area
- Verify assumptions about data structures and types
-
Implement Minimal Fix
- Address the root cause, not just symptoms
- Keep the fix as simple and focused as possible
- Ensure the fix doesn't introduce new issues
- Follow project coding standards and patterns
- Add defensive programming where appropriate
-
Verify and Validate
- Test the fix with original reproduction steps
- Run relevant test suites to ensure no regressions
- Verify edge cases and boundary conditions
- Check for similar issues elsewhere in the codebase
- Document the fix and testing approach
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.
- 2d ago First seen · 186 lines · 0 tokens per session scan A 2e3827de37a1
debugger is an agent published in the GitHub repository FlorianBruniaux/ccboard (94 stars, last pushed 22d ago), licensed MIT. It adds 378 tokens to every session and 2,035 once invoked, about $0.0019 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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issue-tracker
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help
Use this screen to check which agents are alive, what they are running, and where work is currently landing.