get_spec

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

No annotations are provided, so the description carries full burden. It details return shape per spec type (ComponentSpec, PageSpec, DataVizSpec) and error behavior (isError with message). While it does not explicitly state the operation is read-only, 'Fetch' implies idempotence and the error description adds clarity.

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 about 10 sentences, structured into clear paragraphs for prerequisites, return values, error behavior, and usage comparison. It is front-loaded with the primary purpose. While not extremely concise, each sentence adds necessary context.

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?

Given a single parameter, no output schema, and no annotations, the description covers purpose, usage guidelines, prerequisites, return shape per type, error behavior, and sibling differentiation. It leaves no critical gaps for an AI agent to invoke this tool correctly.

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 input schema already describes the 'name' parameter with 100% coverage. The description adds value by noting that the name is case-sensitive and refers to the spec's 'name' field, not the filename, and advising to use get_specs first.

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 opens with a specific action: 'Fetch the full body of a single spec by name.' It clearly identifies the resource and how it differs from its sibling 'get_specs', which returns only names and types.

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 prerequisites (spec must exist, use get_specs to list names) and has a dedicated 'Use this tool vs get_specs' section that explains when to choose each tool, including the use case of reading details before generating code or running analyze_design.

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