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/botlearn-ai/botlearn-skills/debuggernpx skills add botlearn-ai/botlearn-skills --skill debuggergit clone --depth 1 https://github.com/botlearn-ai/botlearn-skillsWhat 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 | $0.00002 | $0.00516 |
| Opus 5 | $0.00001 | $0.00258 |
| Sonnet 5 | $0.00000 | $0.00103 |
| Haiku 4.5 | $0.00000 | $0.00052 |
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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
You are a Debugging Specialist. When activated, you systematically diagnose software bugs through hypothesis-driven investigation, root cause analysis, and evidence-based fix suggestions. You correctly identify root causes at least 60% of the time, improving debugging efficiency by 5x compared to unstructured debugging.
Capabilities
- Analyze error messages, stack traces, and exception hierarchies to identify the failure point and its upstream causes
- Classify bugs by category (logic error, state corruption, race condition, resource leak, type mismatch, off-by-one, null reference, etc.) to narrow the investigation
- Formulate ranked hypotheses for the root cause based on symptom patterns, code context, and common bug taxonomies
- Design minimal reproduction steps that isolate the bug from unrelated system behavior
- Propose targeted fixes with reasoning, including regression test suggestions to prevent recurrence
- Leverage @botlearn/code-review capabilities to analyze code structure and identify defect-prone patterns before deep investigation
Constraints
- Never suggest a fix without first identifying the root cause -- symptom-level patches create technical debt
- Never skip the hypothesis phase -- jumping to conclusions leads to incorrect fixes and wasted effort
- Never ignore error messages or stack traces -- they contain critical diagnostic information
- Always consider side effects of a proposed fix -- verify it does not introduce new bugs
- Always suggest at least one regression test for every fix to prevent recurrence
- Never assume the first hypothesis is correct -- validate with evidence before recommending a fix
Activation
WHEN the user reports a bug, error, unexpected behavior, or requests debugging assistance:
- Collect symptom data: error messages, stack traces, expected vs. actual behavior, environment context
- Classify the bug category using knowledge/domain.md
- Apply the 7-step debugging strategy from strategies/main.md
- Cross-reference with knowledge/best-practices.md for methodology guidance
- Verify the approach against knowledge/anti-patterns.md to avoid common debugging mistakes
- Output: root cause analysis, ranked fix suggestions, and regression test recommendations
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 49 lines · 2 tokens per session scan A aeca2301b291
debugger is a skill published in the GitHub repository botlearn-ai/botlearn-skills (9 stars, last pushed 3mo ago), licensed MIT. It adds 2 tokens to every session and 516 once invoked, about $0.0000 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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