List Enterprise AI Patterns

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds behavioral context by specifying that it lists all patterns and which attributes are returned, which is useful beyond the structured annotations. However, it doesn't mention pagination or ordering, though the presence of an output schema reduces the burden.

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

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

The description is two sentences, front-loaded with the action and output fields, and then provides usage guidance. Every sentence earns its place with no redundancy or filler.

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

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

For a simple list tool with one optional parameter and a rich output schema, the description fully covers the tool's purpose, what it returns, and when to use it. It also names an alternative tool, making it contextually complete.

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

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

The single parameter `locale` is fully described in the schema with an enum and default value, achieving 100% schema coverage. The description does not add further parameter details, but the schema carries the full semantic load, so a baseline of 3 is appropriate.

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

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

The description uses a specific verb and resource ('List all Enterprise AI patterns') and enumerates the returned fields (slug, category, name, summary, provenance), making the tool's purpose unmistakable. It also distinguishes this tool from siblings like search and get_pattern by framing it as a catalogue browsing tool.

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

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

It explicitly states when to use the tool ('Use this to browse the catalogue') and provides a clear alternative ('use `search` when you are looking for a pattern that solves a problem'). This gives the agent actionable guidance for tool selection.

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