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 The-AI-Directory-Company/agents-and-skills --skill debugging-guidegit clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-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/the-ai-directory-company/agents-and-skills/debugging-guide)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/debugging-guide"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/debugging-guide/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/the-ai-directory-company/agents-and-skills/debugging-guide"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/debugging-guide.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 | $0.00030 | $0.01348 |
| Opus 5 | $0.00015 | $0.00674 |
| Sonnet 5 | $0.00006 | $0.00270 |
| Haiku 4.5 | $0.00003 | $0.00135 |
Grade A, and why
debugging-guide 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 8d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging Guide
Before you start
Gather the following before investigating:
- What is the expected behavior? — What should happen
- What is the actual behavior? — What happens instead (exact error message, wrong output, crash)
- When did it start? — Was it always broken, or did it work before a specific change?
- What changed recently? — Deployments, config changes, dependency updates, data migrations
- Who is affected? — All users, specific accounts, specific environments
- Can you reproduce it? — Consistent or intermittent? Steps to trigger?
Do not start guessing at fixes until you can reproduce the bug or have clear evidence of the root cause.
Procedure
1. Reproduce the bug
Before anything else, make the bug happen on demand.
- Follow the exact steps from the bug report
- Use the same environment (OS, browser, API version) as the reporter
- If the bug is intermittent, identify the conditions that increase its likelihood (load, timing, specific data)
- If you cannot reproduce it, gather more data — logs, screenshots, network traces — before proceeding
A bug you cannot reproduce is a bug you cannot verify as fixed.
2. Isolate the scope
Narrow down where the bug lives:
- Layer: Is it frontend, backend, database, infrastructure, or third-party?
- Component: Which module, service, or function?
- Input: Which specific inputs trigger the bug? Which inputs do NOT trigger it?
Techniques for isolation:
- Binary search: Comment out or bypass half the code path. Does the bug persist? Narrow to the half that matters.
- Minimal reproduction: Strip away everything unrelated until you have the smallest code/input that triggers the bug.
- Environment comparison: Does it happen in staging but not local? Diff the configs.
- Git bisect: If it worked before, use
git bisectto find the exact commit that introduced it.
3. Form a hypothesis
State your hypothesis explicitly before testing it:
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.
- 8d ago First seen · 130 lines · 30 tokens per session scan A 6eea9dea10f6
debugging-guide is a skill published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 30 tokens to every session and 1,348 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 2026-09-03.
Other skills, from other repositories
debug-systematic
Systematic 4-phase debugging methodology for complex, intermittent, or mysterious issues. Use when investigating bugs, race conditions, or unexplained failures.
deobfuscating-powershell-obfuscated-malware
Systematically deobfuscate multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure.
detecting-process-injection-techniques
Detects and analyzes process injection techniques used by malware including classic DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading. Uses memory forensics, API monitoring, and behavioral analysis to identify injection artifacts. Activates for requests involving process…
hunting-for-anomalous-powershell-execution
Hunt for malicious PowerShell activity by analyzing Script Block Logging (Event 4104), Module Logging (Event 4103), and process creation events. The analyst parses Windows Event Log EVTX files to detect obfuscated commands, AMSI bypass attempts, encoded payloads, credential dumping keywords, and suspicious download…
mobile-performance-react-native
React Native performance profiling, optimization, and monitoring - JS/UI thread analysis, re-render prevention, list optimization, image performance, bundle size, startup time, memory leaks, React Compiler, New Architecture benefits.
api-observability-axiom-pino-sentry
Pino logging, Sentry error tracking, Axiom - structured logging with correlation IDs, error boundaries, performance monitoring, alerting.