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/berekvolgyipeter/dotclaude/py-debugnpx skills add berekvolgyipeter/dotclaude --skill py-debuggit clone --depth 1 https://github.com/berekvolgyipeter/dotclaudeWhat 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 | $0.00054 | $0.01037 |
| Opus 5 | $0.00027 | $0.00518 |
| Sonnet 5 | $0.00011 | $0.00207 |
| Haiku 4.5 | $0.00005 | $0.00104 |
Grade A, and why
py-debug 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Debugging
Not sure what's wrong? Start with ipdb — step through the code and observe. Once you can characterize the problem (slow, leaking memory, crashing), switch to the matching profiler.
| Problem | Tool |
|---|---|
| Need to step through execution interactively | ipdb |
| Which function is slow? (whole-program overview) | cProfile (stdlib) |
| Identifying slow lines in a function | line-profiler |
| Profile a running process without code changes | py-spy |
| Investigating memory growth or leaks | memory-profiler |
| Hard to read debug output (nested dicts, long lists, tracebacks) | rich |
Behavioral Rules
- Lock the bug with a failing test once reproduced — before patching incorrect behavior, capture the faulty behavior as a regression test (through the public interface where one exists), so the fix is verified and the bug can't silently regress; skip this for pure performance or memory investigations, where a test through the public interface is rarely the right artifact
- Suggest only one tool per problem — don't list all options and ask the user to choose
- Explain the fit in one sentence before showing usage — e.g. "Since you want line-by-line timing,
line-profileris the right tool here." - Prefer
ipdbas the default for general debugging; only reach for profilers when the problem is clearly performance- or memory-related - For performance, start broad then zoom in — use
cProfileto find the slow function, thenline-profilerto find the slow line - Use
py-spywhen you can't modify the code — running process, production, or quick triage - Place
set_trace()just before the suspect line, not at the top of the function - Never add profiling decorators to production code paths — always remind the user to remove them before deploying
Tool Reference
ipdb
Interactive debugger with IPython features (tab completion, syntax highlighting).
import ipdb
ipdb.set_trace() # Pause execution here
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.
- 2d ago First seen · 128 lines · 54 tokens per session scan A 561328b96cef
py-debug is a skill published in the GitHub repository berekvolgyipeter/dotclaude (2 stars, last pushed 20d ago), licensed MIT. It adds 54 tokens to every session and 1,037 once invoked, about $0.0003 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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