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/s977043/river-reviewWrote 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/agents/s977043/river-review/readme)<a href="https://agentmods.dev/agents/s977043/river-review/readme"><img src="https://agentmods.dev/badge/agents/s977043/river-review/readme/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/agents/s977043/river-review/readme"><img src="https://agentmods.dev/badge/agents/s977043/river-review/readme.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 | $0.00000 | $0.00075 |
| Opus 5.5 | $0.00000 | $0.00030 |
| Sonnet 5.5 | $0.00000 | $0.00015 |
| Haiku 4.5 | $0.00000 | $0.00007 |
Grade A, and why
README 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 1mo 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
.claude/agents/
Sub-agent definitions for Claude Code delegation.
| Agent | Purpose | Tools |
|---|---|---|
| river-review | Code review and refactor suggestions | Read, Grep, Glob, Bash |
See docs/agent-layers.md for the 4-layer architecture and cross-tool agent mapping.
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.
- 1mo ago First seen · 10 lines · 0 tokens per session scan A 9711363f8fec
README is an agent published in the GitHub repository s977043/river-review (7 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 75 tokens. 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 agents, from other repositories
smart-contract-auditor
Use when Solidity/EVM contracts exist — after web3 implementation, or /review --contracts (--package before an external audit). Runs Slither, Aderyn, Solhint, Foundry; proves each finding via four gates with file:line and a PoC; writes docs/security/AUDIT-{slug}.md. --package adds a threat model, invariants, a Foundry…
finding-verifier
Batch-verify all findings from one source agent — re-read source, apply false-positive filter, score each 0-100. One verifier per source agent (not per finding).
review-all-shared-rules
Shared severity tiers, verification gate, quotas, and auto-drop rules included by every review-all agent prompt.
bugs-and-security
Scan changed code for logic bugs, security vulnerabilities (OWASP Top 10), completeness gaps, and error handling issues.
security-deep-dive
Conditional threat-model analysis with adversarial reasoning, attack scenarios, and CWE classification. Distinct from agent 02 (which does broad pattern scanning).
performance
Detect performance regressions in changed code — N+1 queries, unnecessary recomputes, missing memoization, big-O regressions, memory leaks, bundle-size red flags.