Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/cyborg-garden/hermes-agent-mt/python-debugpy)<a href="https://agentmods.dev/skills/cyborg-garden/hermes-agent-mt/python-debugpy"><img src="https://agentmods.dev/badge/skills/cyborg-garden/hermes-agent-mt/python-debugpy.svg" alt="Measured on agentmods" 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 | $0.03635 |
| Opus 5 | $0.00009 | $0.01818 |
| Sonnet 5 | $0.00003 | $0.00727 |
| Haiku 4.5 | $0.00002 | $0.00364 |
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 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.
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
95% identical to python-debugpy — 22 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 — 376 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.
- 2d ago First seen · 376 lines · 17 tokens per session scan B ce7e38367ea5
python-debugpy is a skill published in the GitHub repository cyborg-garden/hermes-agent-mt (13 stars, last pushed 5d ago), licensed MIT. It adds 17 tokens to every session and 3,635 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). It is 95% identical to python-debugpy, differing in 22 lines, and is treated as a copy.
Other skills, from other repositories
no-mistakes
Validate your code changes through the no-mistakes pipeline - automated code review, tests, lint, docs, push, PR, and CI - before they reach upstream. Use when the user asks to run no-mistakes, gate or ship or validate their changes, push safely, asks you to do a task and then validate it, or invokes /no-mistakes.
mnemosyne-context
Load this when working on the mnemosyne memory system — its repo, sync server, memory databases, or CI. Covers architecture, the surface/sync data model, dev workflow (tests/ruff/CI matrix), release policy, and known gotchas that are easy to get wrong. Use for any "mnemosyne" dev or devops task, or when a…
hermes-memory-providers
Install and configure Mnemosyne as a Hermes Agent memory provider — local SQLite with vector search, episodic consolidation, and temporal knowledge graphs.
mnemosyne
Persistent cross-session memory via Mnemosyne — store, recall, and consolidate facts, preferences, and context.
mnemosyne-memory-override
Hard rule override that forces Mnemosyne for all durable memory storage. The legacy memory tool is DEPRECATED for user preferences, credentials, and project conventions. Use memory ONLY for ephemeral session state.
trace-harness-launch-failure
Empty session traces mean launch failure, not agent behavior — verify apicallcount/toolcallcount and stdout.txt before analyzing.