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 khasky/awesome-agent-skills --skill awesome-bug-fixgit clone --depth 1 https://github.com/khasky/awesome-agent-skillsWrote 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/khasky/awesome-agent-skills/awesome-bug-fix)<a href="https://agentmods.dev/skills/khasky/awesome-agent-skills/awesome-bug-fix"><img src="https://agentmods.dev/badge/skills/khasky/awesome-agent-skills/awesome-bug-fix/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/khasky/awesome-agent-skills/awesome-bug-fix"><img src="https://agentmods.dev/badge/skills/khasky/awesome-agent-skills/awesome-bug-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00102 | $0.03367 |
| Opus 5 | $0.00051 | $0.01684 |
| Sonnet 5 | $0.00020 | $0.00673 |
| Haiku 4.5 | $0.00010 | $0.00337 |
Grade A, and why
awesome-bug-fix scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- When the obvious loop is not available, walk the ladder — the bug that resists a repro usually needs a different *kind* of loop, not more staring. In rough order of preference: a failing test at whatever seam reaches t How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
Find and fix bugs by following a strict process: no fixes without root cause first.
Why this matters: Random fixes feel faster but often introduce new bugs and leave the original cause in place. A few minutes of real investigation—reproduce, trace, hypothesize—usually leads to one right fix instead of a long chain of patches. It works the same whether you’re in a Node app, a Python script, or a distributed system: understand, then change.
Core Principle
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST. Symptom fixes waste time and introduce new bugs. If you have not completed Phase 1, you may not propose fixes.
Redact before you show anything. This skill quotes commands, outputs and captured artifacts back to the user, and the transcript leaves the machine. Write <REDACTED> in place of every token, password, connection string, cookie and customer identifier; build loops against environment variables so the credential stays in the environment rather than in the command you paste; and from a captured artifact (a HAR file, a log dump, a request trace) quote only the lines carrying the signal, because auth headers ride in the rest. If the redacted output is genuinely not enough to diagnose the bug, say so and ask the user rather than pasting the raw capture.
When to Activate
- User reports a bug, error, or "it doesn't work"
- Test failures, build failures, or integration issues
- Unexpected behavior or performance problems
- User asks to "debug", "find the bug", or "why does X happen"
Use especially when: Under time pressure, "one quick fix" seems obvious, you've already tried multiple fixes, or you don't fully understand the issue. Do not skip for "simple" bugs — simple bugs have root causes too.
If the bug is slowness, memory growth, or throughput — not a wrong result — the diagnostic path is a performance audit, not this correctness loop: call the Skill tool with "awesome-performance-audit" (measure tail latency, take a heap/CPU profile). Return here only once it narrows to a specific, reproducible defect.
What ships with it
1 file 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.
- yesterday Changed 3f52e4dee299
- 6d ago Changed · +12 lines · +5 tokens per session 597092786a4e
- 12d ago First seen · 167 lines · 97 tokens per session scan A f6bd255715eb
awesome-bug-fix is a skill published in the GitHub repository khasky/awesome-agent-skills (8 stars, last pushed 2d ago), licensed MIT. It adds 102 tokens to every session and 3,367 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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