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.
git clone --depth 1 https://github.com/josstei/argus-claudeWrote 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/commands/josstei/argus-claude/welcome)<a href="https://agentmods.dev/commands/josstei/argus-claude/welcome"><img src="https://agentmods.dev/badge/commands/josstei/argus-claude/welcome.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 | $0.00008 | $0.00211 |
| Opus 5 | $0.00004 | $0.00105 |
| Sonnet 5 | $0.00002 | $0.00042 |
| Haiku 4.5 | $0.00001 | $0.00021 |
Grade A, and why
welcome 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 7d 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
Argus Welcome
Display the welcome message and getting started guide.
Output
Display this message:
=====================================
Argus - The All-Seeing Code Reviewer
=====================================
Quick Start:
/argus:review Run review (shows confirmation)
/argus:review --yes Run with defaults (no prompt)
/argus:review --level fast Quick scan with Haiku
/argus:review --external Add detected external validators
Review Levels:
fast Haiku | ~2 min | Quick scan
balanced Sonnet | ~5 min | Standard review
comprehensive Opus | ~8 min | Deep analysis
Settings:
/argus:config View current settings
/argus:config set scope X Set default scope
/argus:config set output X Save reports as markdown/json
Just run /argus:review to get started!
=====================================
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.
- 7d ago First seen · 37 lines · 8 tokens per session scan A 825a0186205e
welcome is a command published in the GitHub repository josstei/argus-claude (6 stars, last pushed 7mo ago), licensed MIT. It adds 8 tokens to every session and 211 once invoked, about $0.0000 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.
Other commands, from other repositories
create-pr
Create GitHub PR from branch — auto-extract ticket, generate title/body, dry-run by default.
discover
Run a full product discovery cycle — from outcome definition through opportunity mapping, prioritisation, and experiment design. Use when the team isn't sure what to build next, or before writing a PRD for a complex feature space.
resume
Resume a previous session. Reads recent session logs, open tasks, and last decisions — gives Claude full context without re-explaining the project.
tax-review
Tax-filing compliance check — invokes tax-reviewer to produce TM-tax-{slug}.md with MeF e-file schema, Form 8879, PTIN/Circular 230, and IRC §7216 consent gaps.
voice-compliance
Voice/telephony compliance check — invokes voice-ai-reviewer to produce TM-voice-{slug}.md with TCPA, STIR/SHAKEN, state recording-consent, EU AI Act Art. 50, and synth-voice deepfake-law gaps.
simplify
The over-engineering review: five tags (delete, stdlib, native, yagni, shrink), a mandatory replacement per finding, and a real null result when there is nothing to cut.