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/vetrox/ventrox/ventrox-reportnpx skills add Vetrox/ventrox --skill ventrox-reportgit clone --depth 1 https://github.com/Vetrox/ventroxWhat 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 | $0.00040 | $0.00659 |
| Opus 5 | $0.00020 | $0.00329 |
| Sonnet 5 | $0.00008 | $0.00132 |
| Haiku 4.5 | $0.00004 | $0.00066 |
Grade A, and why
ventrox-report 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 yesterday.
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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reporter
Call ventrox_vent only after hitting the same friction twice or spending >10 minutes on one task.
Arguments
tried(string, 1–4000 chars): The specific action you took. Example: "run the test suite withuv run pytest".failed(string, 1–4000 chars): What went wrong, with context. Example: "import error onconftest.pythree times in a row; the fix needed PYTHONPATH that no doc states".minutes_lost(0–1440): Time spent on this friction, in minutes.
What to include
- Concrete actions and observed failures.
- Blockers that repeat (same failure ≥2 times or >10 minutes).
What NOT to include
- Fixes, workarounds, or lessons.
- One-off typos or mistakes.
- Questions ("How do I make this faster?").
- Progress notes ("Finished the feature").
Good vents
- tried "run the test suite with
uv run pytest", failed "import error onconftest.pythree times in a row; the fix needed PYTHONPATH that no doc states", minutes_lost 25 - tried "deploy to staging with the standard CloudFormation template", failed "VPC id mismatch in the template; had to edit manually each time for 3 deploys", minutes_lost 18
- tried "install the linter with
pip install ruff", failed "no wheel for Python 3.13 on macOS arm64; built from source twice, flaky on CI", minutes_lost 12 - tried "run database migration with
python manage.py migrate", failed "timeout on the first attempt; docs don't mention --timeout flag; second attempt with flag succeeded", minutes_lost 8
Not vents
- A one-off typo you fixed once. That is not repeated friction.
- "How do I make the tests faster?" That is a question, not friction.
- "Next time use pytest-xdist for parallel tests". That is a lesson or a fix, not what blocked you.
- "Finished the feature, took 3 hours". That is a task-progress note, not friction.
Response
Server returns an id only. Do not expect to read vents back; data stays in the server. Do not ask the user about the vent after writing it; carry on with the task. Use ventrox_edit with that id to correct text in the same session. If you hit rate limit error, stop venting for this session.
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.
- yesterday First seen · 52 lines · 0 tokens per session scan A 70fe899f51af
ventrox-report is a skill published in the GitHub repository Vetrox/ventrox (0 stars, last pushed 10d ago), licensed MIT. It adds 40 tokens to every session and 659 once invoked, about $0.0002 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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