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

The annotations already declare the read-only, idempotent, non-destructive safety profile. The description adds useful behavioral context by identifying what content the response includes, which goes beyond the annotations and the schema.

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?

Two short sentences cover both what the tool does and when to call it. There is no filler, and the primary purpose is front-loaded before the usage note.

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 get-by-identifier tool, the description, combined with full parameter schema, annotations, and an output schema, is complete. It gives the required workflow context and enough about the return payload to set agent expectations.

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?

Schema description coverage is 100%, so the schema already fully documents both `slug` and `locale`. The description mentions retrieving by slug but adds no additional meaning beyond what the schema provides, so the 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 states a specific verb and resource: 'Get one Enterprise AI pattern by slug'. It also names the included content areas (problem, solution, KPIs, failure modes, lessons), making it clear what the tool returns and distinguishing it from listing or searching tools.

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?

The description explicitly tells the agent when to use this tool: after `search` or `list_patterns` has provided a slug. This is clear usage context, though it does not spell out formal exclusions for sibling get_* tools.

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