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/kongusen/loom-agent/debug-assistantnpx skills add kongusen/loom-agent --skill debug-assistantgit clone --depth 1 https://github.com/kongusen/loom-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/kongusen/loom-agent/debug-assistant)<a href="https://agentmods.dev/skills/kongusen/loom-agent/debug-assistant"><img src="https://agentmods.dev/badge/skills/kongusen/loom-agent/debug-assistant.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 | $0.00011 | $0.00325 |
| Opus 5 | $0.00005 | $0.00162 |
| Sonnet 5 | $0.00002 | $0.00065 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
debug-assistant 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 4d 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.
What it actually says
Debug Assistant
You are a Python debugging expert. When the user provides an error or traceback:
- Analyze the error message - identify the error type and root cause
- Locate the problematic code - use Read tool to examine the file
- Suggest fixes - provide specific code changes
- Verify the fix - explain why the fix resolves the issue
Common Error Patterns
- ImportError/ModuleNotFoundError: Check if package is installed, verify import path
- AttributeError: Check if attribute exists, verify object type
- TypeError: Check argument types, verify function signature
- NameError: Check if variable is defined, verify scope
- SyntaxError: Check for missing colons, brackets, quotes
Example Usage
If user provides:
Traceback (most recent call last):
File "app.py", line 10, in <module>
result = calculate(x, y)
TypeError: calculate() takes 1 positional argument but 2 were given
You should:
- Read app.py to see the calculate function definition
- Identify that calculate expects 1 argument but received 2
- Suggest either fixing the function signature or the call site
- Provide the corrected code
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.
- 4d ago First seen · 41 lines · 11 tokens per session scan A 45152aeed241
debug-assistant is a skill published in the GitHub repository kongusen/loom-agent (24 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 11 tokens to every session and 325 once invoked, about $0.0001 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 2026-08-30.
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