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 chriswu727/argus --skill argus-testgit clone --depth 1 https://github.com/chriswu727/argusWrote 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/chriswu727/argus/argus-test)<a href="https://agentmods.dev/skills/chriswu727/argus/argus-test"><img src="https://agentmods.dev/badge/skills/chriswu727/argus/argus-test/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/chriswu727/argus/argus-test"><img src="https://agentmods.dev/badge/skills/chriswu727/argus/argus-test.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 | $0.00045 | $0.00873 |
| Opus 5.5 | $0.00018 | $0.00349 |
| Sonnet 5.5 | $0.00009 | $0.00175 |
| Haiku 4.5 | $0.00005 | $0.00087 |
Grade A, and why
argus-test 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 today.
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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test the application the user is authorized to exercise, using the Argus MCP tools from this plugin.
1. Agree the scope
- Take the URL from the arguments or the conversation. If there is none, ask for it.
- Turn the request into a few concrete goals (user journeys) and constraints.
- Ask before testing anything with real-world effects: purchases, sending messages, deleting or publishing real data, or production systems. Absent permission, record such paths as blocked rather than exercising them.
2. Check the environment
Call start_session with the URL, goals and constraints. If it fails with a
browser-launch error, tell the user and offer to install the matching browser.
Run it only after they agree, because it downloads software:
uvx --python 3.12 --from argus-testing==0.12.0 --with playwright==1.64.1 python -m playwright install chromium
For other setup problems, run uvx --python 3.12 --from argus-testing==0.12.0 argus-mcp --doctor;
it prints the fix for each failed check. Then call start_session again.
3. Test
Follow the protocol that start_session returns. In short: mark the goals you
are about to walk in_progress with coverage_update and walk each journey with
real state. For a click that should change something (add, complete, delete,
save), use test_action with an expect prediction, such as
{"removes": "Buy groceries"} or {"count": {"label": "tasks", "delta": 1}}.
A SURPRISE is a lead to verify, not yet a bug.
Text alone hides many problems, so look at each key page as a user would at
least once per journey: take a screenshot and judge it. Watch for the main
action styled weaker than a secondary one, urgency, stock or discount claims
that the prices do not support, odd field order, labels that contradict each
other (a field marked required but labelled optional), and prices or totals
that disagree between pages. Run check_layout for overflow and clipped text.
Record such judgments with record_observation; use record_bug with verify
only when a text check on a fresh load can confirm the symptom.
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.
- today Changed 7b384210aea6
- 2d ago First seen · 75 lines · 45 tokens per session scan A 3f5a0b77e182
argus-test is a skill published in the GitHub repository chriswu727/argus (4 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 873 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-28.
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