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 Owl-Listener/ai-design-skills --skill agent-role-designgit clone --depth 1 https://github.com/Owl-Listener/ai-design-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/owl-listener/ai-design-skills/agent-role-design)<a href="https://agentmods.dev/skills/owl-listener/ai-design-skills/agent-role-design"><img src="https://agentmods.dev/badge/skills/owl-listener/ai-design-skills/agent-role-design/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/owl-listener/ai-design-skills/agent-role-design"><img src="https://agentmods.dev/badge/skills/owl-listener/ai-design-skills/agent-role-design.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 | $0.00021 | $0.00563 |
| Opus 5 | $0.00010 | $0.00282 |
| Sonnet 5 | $0.00004 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
agent-role-design 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 12d 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 — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Role Design
In a multi-agent system, each agent needs a clearly defined role — what it does, what it knows, what it's responsible for, and where its authority ends. Without clear roles, agents duplicate work, conflict with each other, or leave gaps.
Defining an Agent Role
For each agent in the system, specify:
- Purpose: What is this agent for? One sentence describing its reason to exist.
- Capabilities: What can this agent do? List specific actions and outputs.
- Knowledge scope: What does this agent know about? What domains, data, and context does it have access to?
- Authority: What decisions can this agent make autonomously? What requires approval?
- Boundaries: What is explicitly outside this agent's scope? Where does it stop and hand off?
- Success criteria: How do you know this agent is doing its job well?
Role Design Principles
- Single responsibility: Each agent should have one clear purpose. If you need a paragraph to explain what it does, it's doing too much.
- Clear boundaries: The line between one agent's scope and another's should be unambiguous. No overlapping authority without explicit conflict resolution.
- Minimal coupling: Agents should be able to do their work with minimal dependencies on other agents. Share results, not process.
- Appropriate autonomy: The level of autonomous decision-making should match the stakes and the agent's reliability in that domain.
Role Patterns
- Specialist: Deep expertise in one domain. Handles all tasks of a specific type.
- Router: Doesn't do work itself but directs tasks to the right specialist.
- Orchestrator: Manages the overall workflow, coordinates between specialists.
- Validator: Reviews other agents' outputs for quality, safety, or compliance.
- Fallback: Handles cases that other agents can't or won't.
Role Conflicts
When agents' roles overlap or conflict:
- Priority rules: When two agents could handle a task, which one gets it?
- Escalation paths: When agents disagree, who decides?
- Shared resources: When agents need the same data or tools, how is access managed?
- Feedback loops: How do agents inform each other about what they've done?
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.
- 12d ago First seen · 38 lines · 21 tokens per session scan A 37b06b435363
agent-role-design is a skill published in the GitHub repository Owl-Listener/ai-design-skills (173 stars, last pushed 3mo ago), licensed MIT. It adds 21 tokens to every session and 563 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.
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