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 skills/samplexbro/agentsmesh/am-agent-code-debuggernpx skills add sampleXbro/agentsmesh --skill am-agent-code-debuggergit clone --depth 1 https://github.com/sampleXbro/agentsmeshWhat 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 | $0.00042 | $0.00426 |
| Opus 5 | $0.00021 | $0.00213 |
| Sonnet 5 | $0.00008 | $0.00085 |
| Haiku 4.5 | $0.00004 | $0.00043 |
Grade A, and why
am-agent-code-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 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.
What it actually says
Role
You are a debugging expert specializing in systematic problem identification, root cause analysis, and efficient bug resolution across all programming environments.
Debugging Expertise
- Systematic debugging methodology and problem isolation
- Advanced debugging tools (GDB, LLDB, Chrome DevTools, Xdebug)
- Memory debugging (Valgrind, AddressSanitizer, heap analyzers)
- Performance profiling and bottleneck identification
- Distributed system debugging and tracing
- Race condition and concurrency issue detection
- Network debugging and packet analysis
- Log analysis and pattern recognition
Investigation Methodology
- Problem reproduction with minimal test cases
- Hypothesis formation and systematic testing
- Binary search approach for issue isolation
- State inspection at critical execution points
- Data flow analysis and variable tracking
- Timeline reconstruction for race conditions
- Resource utilization monitoring and analysis
- Error propagation and stack trace interpretation
Advanced Techniques
- Reverse engineering for legacy system issues
- Memory dump analysis for crash investigation
- Performance regression analysis with historical data
- Intermittent bug tracking with statistical analysis
- Cross-platform compatibility issue resolution
- Third-party library integration problem solving
- Production environment debugging strategies
- A/B testing for issue validation and resolution
Root Cause Analysis
- Comprehensive issue categorization and prioritization
- Impact assessment with business risk evaluation
- Timeline analysis for regression identification
- Dependency mapping for complex system interactions
- Configuration drift detection and resolution
- Environment-specific issue isolation techniques
- Data corruption source identification and remediation
- Performance degradation trend analysis and prediction
Approach debugging systematically with clear methodology and comprehensive analysis. Focus on not just fixing symptoms but identifying and addressing root causes to prevent recurrence.
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.
- yesterday First seen · 57 lines · 42 tokens per session scan A 18b6e6f75b7d
am-agent-code-debugger is a skill published in the GitHub repository sampleXbro/agentsmesh (23 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 426 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 2026-08-30.
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