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 agents/cotal-ai/cotal/linusgit clone --depth 1 https://github.com/Cotal-AI/CotalWrote 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/cotal-ai/cotal/linus)<a href="https://agentmods.dev/agents/cotal-ai/cotal/linus"><img src="https://agentmods.dev/badge/agents/cotal-ai/cotal/linus.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 | $0.00016 | $0.00118 |
| Opus 5 | $0.00008 | $0.00059 |
| Sonnet 5 | $0.00003 | $0.00024 |
| Haiku 4.5 | $0.00002 | $0.00012 |
Grade A, and why
linus 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 4d 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
You are a reviewer on a shared mesh of peer agents — lateral peers, no orchestrator above you. When a peer hands off a change, review it and reply with a clear verdict: what's good, what must change, and why. Be specific and direct. If you're idle, say so in your presence so the planner knows you can take the next 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.
- 4d ago First seen · 14 lines · 16 tokens per session scan A 2b208f4f77e4
linus is an agent published in the GitHub repository Cotal-AI/Cotal (258 stars, last pushed today), licensed Apache-2.0. It adds 16 tokens to every session and 118 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 2026-08-30.
Other agents, from other repositories
code-quality-reviewer
Code quality reviewer: bug detection, security vulnerabilities, performance issues, linting, type checking, test coverage.
a2a
One agent invoking another is delegation; A2A is the transport binding used when the target is outside your platform, and this page separates the two.
context-strategies
Three settings — static, hybrid and dynamic — decide whether large tool outputs are offloaded to object storage, whether compacted history is preserved, and whether tools are disclosed lazily.
planner
Planning gateway for multi-agent Bindu collaboration.
skills
A skill is a folder of files an agent loads only when a task calls for it — this page covers the three tiers of disclosure, where the files land, and what the model is told at each stage.
what-is-an-agent
An agent is a workspace-scoped definition — an instruction, a model, a tool list and attached skills — and this page separates what it configures from what governs it.