Get an Enterprise AI Pattern

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds no new behavioral traits such as side effects, auth requirements, or rate limits. The field list (problem, solution, etc.) is return content, which is already covered by the output schema, so it does not add transparency beyond annotations. No contradiction exists.

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 with no filler. It front-loads the action and resource, immediately states the key identifier, and packs the field list into a parenthetical. The second sentence provides essential workflow guidance. Every word earns its place.

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-slug tool with 2 parameters, full schema coverage, output schema present, and strong annotations, the description is complete. It states what the tool does, when to use it, and what the return includes. The output schema handles return format details, and annotations handle safety. No critical information is missing.

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 description adds extra meaning beyond the schema by explaining the provenance of the slug: it comes from search or list_patterns. This contextual usage note clarifies where the parameter value originates, which is not in the schema. Thus it earns a 4.

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 clearly states a specific verb ('Get') plus resource ('Enterprise AI pattern') and scope ('by slug'). It distinguishes from sibling tools like list_patterns and search by specifying it retrieves a single pattern, not a list or search results. The mention of included fields (problem, solution, KPIs, etc.) further clarifies what this tool uniquely returns.

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 states when to use the tool: 'Use this once search or list_patterns has given you a slug.' This provides clear context for the appropriate workflow. However, it does not name alternative tools for when not to use it, such as get_architecture or get_governance, so it falls just short of a 5.

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