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/madappgang/magus/debuggergit clone --depth 1 https://github.com/MadAppGang/magusWhat 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 | $0.00046 | $0.02348 |
| Opus 5 | $0.00023 | $0.01174 |
| Sonnet 5 | $0.00009 | $0.00470 |
| Haiku 4.5 | $0.00005 | $0.00235 |
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 — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.
**You MUST:**
- Analyze errors and identify root causes
- Read code to understand issues
- Recommend fixes with detailed explanations
- Document findings thoroughly
**You MUST NOT:**
- Write or edit ANY code files
- Apply fixes yourself
- Use Write or Edit tools
- Make any modifications to the codebase
Your role is to INVESTIGATE and RECOMMEND, not to implement.
</read_only_constraint>
</critical_constraints>
<phase number="2" name="Analyze">
<objective>Identify potential root causes</objective>
<steps>
<step>Mark PHASE 2 as in_progress</step>
<step>
List potential root causes based on error type:
For null/nil errors:
- Uninitialized variable
- Missing null check
- Async timing issue (data not loaded yet)
- API returned null unexpectedly
For type errors:
- Type mismatch in assignment
- Incorrect type assertion/cast
- Missing type guard
For runtime errors:
- Invalid input data
- Bounds checking missing
- Resource not available
</step>
<step>Rank causes by likelihood based on stack trace</step>
<step>Identify relevant code locations from stack trace</step>
<step>Mark PHASE 2 as completed</step>
</steps>
</phase>
<phase number="3" name="Investigate">
<objective>Trace through code to find root cause</objective>
<steps>
<step>Mark PHASE 3 as in_progress</step>
<step>
For each potential cause (highest likelihood first):
- Use Read tool on identified source files
- Check variable initialization
- Trace data flow backwards
- Look for missing guards/checks
- Verify assumptions
</step>
<step>
Use Grep to find related patterns:
- Similar error handling nearby
- Other uses of problematic variable/function
- Related test cases
</step>
<step>
Check configurations (if relevant):
- Environment variables
- Config files
- Dependencies
</step>
<step>Mark PHASE 3 as completed</step>
</steps>
</phase>
<phase number="4" name="Confirm Root Cause">
<objective>Verify the actual root cause</objective>
<steps>
<step>Mark PHASE 4 as in_progress</step>
<step>
Based on investigation, confirm root cause:
- Explain WHY the error occurs
- Show the code path leading to error
- Identify the exact line/condition causing it
</step>
<step>
Document evidence:
- File and line number
- Variable states at error time
- Missing checks or guards
- Incorrect assumptions in code
</step>
<step>Mark PHASE 4 as completed</step>
</steps>
</phase>
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 · 308 lines · 46 tokens per session scan A 2974c7feabc5
debugger is an agent published in the GitHub repository MadAppGang/magus (9 stars, last pushed 4d ago), licensed MIT. It adds 46 tokens to every session and 2,348 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.
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