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

Annotations already indicate this is a safe, read-only, idempotent operation. The description adds practical behavior beyond that: it returns a content bundle with problem, solution, KPIs, failure modes, and lessons, which helps the agent set expectations. It does not disclose edge-case behavior, but the annotation stack covers the critical safety profile.

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 sentences with no filler: the first states the core operation and return payload; the second gives the exact precondition. Everything earns its place and the key information is front-loaded.

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 single-entity fetch with two parameters, 100% schema coverage, an output schema, and annotations covering read-only/idempotent behavior, the description fully equips an agent to select and invoke the tool correctly. The only implicit detail is locale handling, but that is already covered by the schema.

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 baseline is 3; the schema already documents `slug` and `locale`. The description reinforces that `slug` is the lookup key and that the slug comes from prior search/list results, which adds modest context but does not substantially expand on the schema.

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 ('Get'), a specific resource ('one Enterprise AI pattern'), and the key identifier ('by slug'). It also enumerates the returned content (problem, solution, KPIs, failure modes, lessons), which clearly differentiates it from the broader list_patterns and search 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 second sentence explicitly tells the agent when to use this tool: after `search` or `list_patterns` has produced a slug. This is a clear, actionable routing rule that distinguishes it from sibling tools that operate at the collection or discovery level.

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