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 Bilal140202/the-lord-of-the-skills --skill vstorm-co__pydantic-deepagentsgit clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-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/bilal140202/the-lord-of-the-skills/vstorm-co__pydantic-deepagents)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/vstorm-co__pydantic-deepagents"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/vstorm-co__pydantic-deepagents/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/bilal140202/the-lord-of-the-skills/vstorm-co__pydantic-deepagents"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/vstorm-co__pydantic-deepagents.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 | $0.00013 | $0.00711 |
| Opus 5 | $0.00006 | $0.00356 |
| Sonnet 5 | $0.00003 | $0.00142 |
| Haiku 4.5 | $0.00001 | $0.00071 |
Grade A, and why
systematic-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 9d 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.
This is a copy
100% identical to systematic-debugging — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
A structured approach to finding and fixing bugs.
The Debugging Loop
1. REPRODUCE → 2. ISOLATE → 3. DIAGNOSE → 4. FIX → 5. VERIFY
Never skip steps. Never guess-and-check repeatedly.
Step 1: Reproduce
- Run the exact command that fails
- Capture FULL output (stdout AND stderr)
- Note: exit code, error message, stack trace
- If intermittent, identify what changes between runs
Step 2: Isolate
- What's the MINIMAL input that triggers the error?
- Which specific line/function fails? (read the traceback bottom-up)
- Is it a compile error, runtime error, or wrong output?
- Does it fail on all inputs or specific ones?
Step 3: Diagnose
Read the error message carefully
| Error type | Where to look |
|---|---|
| Compile error | The FIRST error (later ones are often cascading) |
| Segfault | Last function in the stack trace, check array bounds and null pointers |
| Python traceback | The innermost frame (bottom), but also check the middle for context |
| Wrong output | Diff expected vs actual: diff <(expected) <(actual) |
| Timeout/hang | Is it an infinite loop? Deadlock? I/O bound? Add a timer or counter |
Add minimal instrumentation
- C:
fprintf(stderr, "reached checkpoint %d\n", __LINE__); - Python:
print(f"DEBUG: {var=}", file=sys.stderr) - Check intermediate values, not just final output
- Remove debug prints after fixing
Step 4: Fix
- Change ONE thing at a time
- If the same approach fails 3 times → completely different strategy
- Don't add workarounds — fix the root cause
- Common root causes:
- Off-by-one errors (loop bounds, array indexing)
- Type mismatches (int vs float, signed vs unsigned)
- Encoding issues (UTF-8 vs bytes)
- Path errors (relative vs absolute, missing trailing slash)
- Race conditions (file not written yet, process not started)
Step 5: Verify
- Run the same command that failed before
- Test with multiple inputs, not just the one that was failing
- Check edge cases: empty input, single element, very large input
- Run any existing test suite
What ships with it
15 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.
- 9d ago First seen · 89 lines · 13 tokens per session scan A 1f65a08595e6
systematic-debugging is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (4 stars, last pushed 6d ago), licensed MIT. It adds 13 tokens to every session and 711 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to systematic-debugging, differing in 0 lines, and is treated as a copy.
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