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/review)<a href="https://agentmods.dev/commands/josstei/argus-claude/review"><img src="https://agentmods.dev/badge/commands/josstei/argus-claude/review.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 | $0.00012 | $0.02183 |
| Opus 5 | $0.00006 | $0.01092 |
| Sonnet 5 | $0.00002 | $0.00437 |
| Haiku 4.5 | $0.00001 | $0.00218 |
Grade A, and why
review 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.
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Argus Code Review
Multi-agent code review orchestrator with cross-validation from multiple LLM providers.
Configuration
Step 1: Parse Arguments and Load Config
- Parse
$ARGUMENTSfor:--level <fast|balanced|comprehensive>- Skip confirmation prompt--scope <path>- Override scope directory--output <format>- Override output format--yesor-y- Accept defaults without confirmation--external- Detect external validators and add any detected tools tovalidators
- Load
defaults.jsonfor review levels and options - Default to
balancedlevel
Step 2: Confirmation or Execute
If --level OR --yes provided: Skip to Step 3 (no prompt)
Otherwise, show confirmation prompt:
Argus Code Review
=================
Ready to run with:
Level: Balanced (Sonnet, ~5 min)
Scope: {detected_scope}
Output: inline
[1] Change level [2] Change scope [3] Change output [Enter] Start [Q] Cancel
Handle input:
- Enter/empty → proceed with shown settings
- 1 → prompt for level (fast/balanced/comprehensive)
- 2 → prompt for scope path
- 3 → prompt for output format (inline/markdown/json)
- Q/q → abort review
Step 3: Apply Selected Level
Load the settings from the selected review level:
model- Claude model for agentsdepth- Which phases to runstrictness- Issue sensitivity thresholdvalidators- Validation providersoutput- Output format (can be overridden by --output)
If --external is set, detected tools are appended to validators in Step 6.
Step 4: Smart Scope Detection
If scope is "auto" (default), detect in order:
- Check if
src/exists → usesrc/ - Check if
lib/exists → uselib/ - Check if
app/exists → useapp/ - Check if
packages/exists → usepackages/(monorepo) - Fall back to
.(current directory)
Step 5: Display Summary and Start
Argus Code Review
=================
Level: {selected level}
Model: {config.model}
Scope: {detected or config.scope}
Phases: {phases based on depth}
Starting review...
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 · 279 lines · 12 tokens per session scan A 0e9b73d6a5d2
review is a command published in the GitHub repository josstei/argus-claude (6 stars, last pushed 7mo ago), licensed MIT. It adds 12 tokens to every session and 2,183 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 2026-08-31.
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.
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.
git
The pre-finish status: branch, hygiene findings, message checks, workflow lint, template state.