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 skills add krzysztofsurdy/code-virtuoso --skill debugginggit clone --depth 1 https://github.com/krzysztofsurdy/code-virtuosoWrote 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/skills/krzysztofsurdy/code-virtuoso/debugging)<a href="https://agentmods.dev/skills/krzysztofsurdy/code-virtuoso/debugging"><img src="https://agentmods.dev/badge/skills/krzysztofsurdy/code-virtuoso/debugging/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/skills/krzysztofsurdy/code-virtuoso/debugging"><img src="https://agentmods.dev/badge/skills/krzysztofsurdy/code-virtuoso/debugging.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 | $0.00083 | $0.02429 |
| Opus 5.5 | $0.00033 | $0.00972 |
| Sonnet 5.5 | $0.00017 | $0.00486 |
| Haiku 4.5 | $0.00008 | $0.00243 |
Grade A, and why
debugging 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.
How it starts
The opening of the file, as written. The whole thing — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging
Systematic methodology for finding and fixing bugs. Prioritizes root cause analysis over symptom treatment, evidence over intuition, and prevention over recurrence.
Iron Law
No fix without root cause. Never apply a fix until you can explain WHY the bug exists, not just WHERE it manifests. Symptom-level fixes create new bugs.
When to Use
- Bug report from QA or production alert
- Test failure with unclear cause
- Intermittent/flaky behavior
- Performance degradation
- Unexpected behavior that "used to work"
- Integration failures between components
Workflow
Phase 1: Reproduce
Establish a reliable reproduction before investigating.
- Collect all evidence — error messages, stack traces, logs, screenshots, user steps
- Identify the exact conditions: environment, data state, user actions, timing
- Create a minimal reproduction — strip away everything that isn't needed to trigger the bug
- Confirm reproduction is consistent (if intermittent, note frequency and conditions)
- Write down the reproduction steps precisely — someone else should be able to follow them
Output: Documented reproduction steps, minimal test case
If you cannot reproduce: Document what you tried, check environment differences, add instrumentation and wait for next occurrence. Do not proceed to Phase 2 on guesswork — unreproducible bugs get logged, not "fixed."
Phase 2: Investigate
Gather evidence systematically. Do NOT form hypotheses yet — this phase is about observation, not explanation.
- Read the full error message and stack trace — every line, not just the first one
- Check git history — what changed recently? (
git log --since="2 weeks ago",git bisect) - Trace the data flow — follow the input from entry point to failure point
- Check boundaries — where does data cross component/service/layer boundaries?
- Collect environmental context — versions, configuration, dependencies, resource state
- Map the blast radius — what else is affected? Is this an isolated failure or systemic?
What ships with it
2 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.
- 1mo ago First seen · 244 lines · 83 tokens per session scan A 8a57b6ad6faf
debugging is a skill published in the GitHub repository krzysztofsurdy/code-virtuoso (39 stars, last pushed 5mo ago), licensed MIT. It adds 83 tokens to every session and 2,429 once invoked, about $0.0003 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 2026-08-30.
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