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 seaworld008/Commonly-used-high-value-skills --skill agent-designergit clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-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/seaworld008/commonly-used-high-value-skills/agent-designer)<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/agent-designer"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/agent-designer/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/seaworld008/commonly-used-high-value-skills/agent-designer"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/agent-designer.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 | $0.00027 | $0.02564 |
| Opus 5 | $0.00014 | $0.01282 |
| Sonnet 5 | $0.00005 | $0.00513 |
| Haiku 4.5 | $0.00003 | $0.00256 |
Grade A, and why
agent-designer 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.
This is a copy
95% identical to agent-designer — 50 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Designer - Multi-Agent System Architecture
When to Use
Use this skill when the user wants to:
- design a multi-agent system or agent topology
- compare orchestration patterns for agents
- define agent roles, tool boundaries, or communication protocols
- evaluate safety, scaling, and failure-handling trade-offs in an agent architecture
Usage
Recommended flow:
analyze requirements
-> choose architecture pattern
-> define agent roles and interfaces
-> design communication and safety mechanisms
-> specify evaluation and scaling strategy
Minimal Design Skeleton
system:
pattern: supervisor
agents:
- name: coordinator
role: routes work and aggregates results
- name: researcher
role: gathers evidence
- name: implementer
role: executes bounded changes
Tier: POWERFUL
Category: Engineering
Tags: AI agents, architecture, system design, orchestration, multi-agent systems
Overview
Agent Designer is a comprehensive toolkit for designing, architecting, and evaluating multi-agent systems. It provides structured approaches to agent architecture patterns, tool design principles, communication strategies, and performance evaluation frameworks for building robust, scalable AI agent systems.
Core Capabilities
1. Agent Architecture Patterns
Single Agent Pattern
- Use Case: Simple, focused tasks with clear boundaries
- Pros: Minimal complexity, easy debugging, predictable behavior
- Cons: Limited scalability, single point of failure
- Implementation: Direct user-agent interaction with comprehensive tool access
Supervisor Pattern
- Use Case: Hierarchical task decomposition with centralized control
- Architecture: One supervisor agent coordinating multiple specialist agents
- Pros: Clear command structure, centralized decision making
- Cons: Supervisor bottleneck, complex coordination logic
- Implementation: Supervisor receives tasks, delegates to specialists, aggregates results
What ships with it
13 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.
- agent_evaluator.py 52 KB runs code
- agent_planner.py 38 KB runs code
- assets/sample_execution_logs.json 15 KB
- assets/sample_system_requirements.json 2.2 KB
- assets/sample_tool_descriptions.json 16 KB
- expected_outputs/sample_agent_architecture.json 14 KB
- expected_outputs/sample_evaluation_report.json 15 KB
- expected_outputs/sample_tool_schemas.json 12 KB
- README.md 12 KB
- references/agent_architecture_patterns.md 9.6 KB
- references/evaluation_methodology.md 20 KB
- references/tool_design_best_practices.md 13 KB
- tool_schema_generator.py 37 KB runs code
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 Changed · +6 tokens per session bd6dac16d7db
- 8d ago Changed 34a40ae872b0
- 12d ago First seen · 325 lines · 21 tokens per session scan A 8563d0a91d42
agent-designer is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (70 stars, last pushed 4d ago), licensed MIT. It adds 27 tokens to every session and 2,564 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to agent-designer, differing in 50 lines, and is treated as a copy.
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