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list_patterns

Retrieve available orchestration patterns for GPT subagents to guide reviews, audits, threat modeling, and large analyses. Each pattern includes name, title, summary, and usage guidance.

Instructions

List available orchestration patterns for driving the GPT subagents. Call this before non-trivial expert work — reviews, audits, threat modeling, large analysis — then read the chosen one with get_pattern. Returns each pattern's name, title, summary, and when to use it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses that it lists patterns and returns each pattern's name, title, summary, and when to use it. It implies a read-only operation, though not explicitly stated. Sufficient for a simple list tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words. First states core function, second adds usage guidance and return details. Efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters and no output schema, the description covers purpose, when to use, what to do next, and what it returns. Complete for its simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist; schema coverage is 100%. The description correctly avoids parameter details. Baseline 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List', the resource 'available orchestration patterns', and the context 'for driving the GPT subagents'. It differentiates from siblings by mentioning subsequent use of get_pattern.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to call this before non-trivial expert work (reviews, audits, etc.) and then read the chosen pattern with get_pattern. Provides clear when-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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