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 Tyler-R-Kendrick/agent-skills --skill cagentgit clone --depth 1 https://github.com/Tyler-R-Kendrick/agent-skillsWrote 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/tyler-r-kendrick/agent-skills/cagent)<a href="https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/cagent"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/cagent/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/tyler-r-kendrick/agent-skills/cagent"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/cagent.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 | $0.00094 | $0.01251 |
| Opus 5 | $0.00047 | $0.00626 |
| Sonnet 5 | $0.00019 | $0.00250 |
| Haiku 4.5 | $0.00009 | $0.00125 |
Grade A, and why
cagent 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 11d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
cagent — Docker Agent Runtime
Overview
cagent is an open-source multi-agent runtime from Docker that lets you define, orchestrate, and run teams of AI agents. Agents are configured in YAML with specialized capabilities, tools, and sub-agents. cagent supports MCP for tool integration, the Agent Client Protocol (ACP) for IDE integration, and runs locally via cagent run. Bundled in Docker Desktop.
Installation
# Bundled with Docker Desktop, or install standalone:
brew install docker/tap/cagent # macOS
# Or download from github.com/docker/cagent/releases
Agent Configuration
Agents are defined in a cagent.yaml file:
version: "2"
agents:
root:
model: anthropic/claude-sonnet-4-5-20250929
description: A helpful AI assistant with search and file access
instruction: |
You are a knowledgeable assistant that helps users with various tasks.
Be helpful, accurate, and concise in your responses.
Write your results to disk.
toolsets:
- type: mcp
ref: docker:duckduckgo
- type: mcp
command: rust-mcp-filesystem
args: ["--allow-write", "."]
tools: ["read_file", "write_file"]
Model Configuration
Define models inline or as named references:
version: "2"
models:
fast:
provider: openai
model: gpt-5-mini
max_tokens: 4096
strong:
provider: anthropic
model: claude-sonnet-4-5-20250929
max_tokens: 64000
agents:
root:
model: strong
description: Main orchestrator
sub_agents: [researcher, writer]
researcher:
model: fast
description: Finds information
toolsets:
- type: mcp
ref: docker:duckduckgo
writer:
model: strong
description: Writes polished content
MCP Tool Integration
Docker MCP Gateway
Use containerized MCP servers via Docker's MCP Gateway:
toolsets:
- type: mcp
ref: docker:duckduckgo # Search
- type: mcp
ref: docker:fetch # HTTP fetch
- type: mcp
ref: docker:github # GitHub API
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- AGENTS.md 4.2 KB
- metadata.json 640 B
- README.md 646 B
- rules/_sections.md 1.3 KB
- rules/_template.md 365 B
- rules/cagent-define-named-model-references-in-the-models-section-to.md 413 B
- rules/cagent-keep-agent-instructions-focused.md 329 B
- rules/cagent-start-with-a-single-root-agent-and-add-sub-agents-only.md 377 B
- rules/cagent-use-docker-mcp-gateway-ref.md 314 B
- rules/cagent-use-the-memory-toolset-with-a-persistent-path-for-agents.md 398 B
- rules/cagent-use-the-think-toolset-for-agents-that-need-to-reason.md 381 B
- rules/cagent-use-tools.md 291 B
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.
- 11d ago First seen · 175 lines · 94 tokens per session scan A 796a5678df4f
cagent is a skill published in the GitHub repository Tyler-R-Kendrick/agent-skills (11 stars, last pushed 3mo ago), licensed MIT. It adds 94 tokens to every session and 1,251 once invoked, about $0.0005 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.
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