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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context by detailing the exact contents of the return and emphasizing that the tool is 'descriptive, not advisory,' which helps the agent understand how to interpret the output. No contradictions with annotations.

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 information-dense but well-structured, front-loading the core action and then enumerating the return contents. The final sentences provide usage guidance and a concise nickname. It is slightly long but every sentence contributes meaning.

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 the tool's complexity, the description comprehensively covers what the tool returns, how to get a slug, and how to interpret the results (descriptive vs advisory). With an output schema present, the description need not detail return value types, making this quite 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 schema already provides 100% coverage for the single parameter 'slug' with guidance to use list_investment_theses(). The description reinforces this and adds context about the output but does not offer additional parameter-level semantics beyond 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 clearly states the tool returns the complete thesis for a given slug, enumerating the economic framework, portfolio construction, and stress evidence. It explicitly distinguishes itself from list_investment_theses (discovery) and describes itself as the 'instant portfolio with all tested attributes'.

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 provides a clear usage context: use this tool to retrieve a full case study for a known slug, and discover valid slugs via list_investment_theses(). It also clarifies that the output is descriptive and not advisory, leaving suitability to the agent. However, it does not explicitly state when not to use the tool or mention alternatives.

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