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 aivrar/portable-hermes-agent --skill python-debugpygit clone --depth 1 https://github.com/aivrar/portable-hermes-agentWrote 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/aivrar/portable-hermes-agent/python-debugpy)<a href="https://agentmods.dev/skills/aivrar/portable-hermes-agent/python-debugpy"><img src="https://agentmods.dev/badge/skills/aivrar/portable-hermes-agent/python-debugpy/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/aivrar/portable-hermes-agent/python-debugpy"><img src="https://agentmods.dev/badge/skills/aivrar/portable-hermes-agent/python-debugpy.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 | $0.00017 | $0.03617 |
| Opus 5.5 | $0.00007 | $0.01447 |
| Sonnet 5.5 | $0.00003 | $0.00723 |
| Haiku 4.5 | $0.00002 | $0.00362 |
Grade B, and why
python-debugpy scanned grade B 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 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
echo 0 | sudo tee /proc/sys/kernel/yama/ptrace_scope This is a copy
100% identical to python-debugpy — 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 — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Debugger (pdb + debugpy)
Overview
Three tools, picked by situation:
| Tool | When |
|---|---|
breakpoint() + pdb |
Local, interactive, simplest. Add breakpoint() in the source, run normally, get a REPL at that line. |
python -m pdb |
Launch an existing script under pdb with no source edits. Useful for quick poking. |
debugpy |
Remote / headless / "attach to already-running process." Talks DAP, scriptable from terminal, works for long-lived processes (gateway, daemon, PTY children). |
Start with breakpoint(). It's the cheapest thing that works.
When to Use
- A test fails and the traceback doesn't reveal why a value is wrong
- You need to step through a function and watch a collection mutate
- A long-running process (hermes gateway, tui_gateway) misbehaves and you can't restart it
- Post-mortem: an exception fired in prod-ish code and you want to inspect locals at the crash site
- A subprocess / child (Python
_SlashWorker, PTY bridge worker) is the actual bug site
Don't use for: things print() / logging.debug solve in under a minute, or things pytest -vv --tb=long --showlocals already reveals.
pdb Quick Reference
Inside any pdb prompt ((Pdb)):
| Command | Action |
|---|---|
h / h cmd |
help |
n |
next line (step over) |
s |
step into |
r |
return from current function |
c |
continue |
unt N |
continue until line N |
j N |
jump to line N (same function only) |
l / ll |
list source around current line / full function |
w |
where (stack trace) |
u / d |
move up / down in the stack |
a |
print args of the current function |
p expr / pp expr |
print / pretty-print expression |
display expr |
auto-print expr on every stop |
b file:line |
set breakpoint |
b func |
break on function entry |
b file:line, cond |
conditional breakpoint |
cl N |
clear breakpoint N |
tbreak file:line |
one-shot breakpoint |
!stmt |
execute arbitrary Python (assignments included) |
interact |
drop into full Python REPL in current scope (Ctrl+D to exit) |
q |
quit |
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 · 374 lines · 17 tokens per session scan B 24258d93eb08
python-debugpy is a skill published in the GitHub repository aivrar/portable-hermes-agent (236 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 3,617 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). It is 100% identical to python-debugpy, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
python-debugpy
Debug Python with pdb, breakpoint(), post-mortem inspection, and debugpy remote or headless attach.
flask-werkzeug-attack
Exploit Flask/Werkzeug debugger exposure for traceback and SECRET leaks.
pytorch-lightning
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.
jupyter-live-kernel
Iterative Python via live Jupyter kernel (hamelnb).
python-code-quality
Code quality checks, linting, formatting, and type checking commands for the Agent Framework Python codebase. Use this when running checks, fixing lint errors, or troubleshooting CI failures.
plugin-architecture-patterns
Design, implement, or diagnose Xberg plugin traits, typed registries, priority collisions, lifecycle, native extractors, and Alef-generated Python plugin bridges. Load for plugin-system work, not ordinary extractor parsing.