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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the content of the thesis but not the return structure, data freshness, limitations, or any operational context. This under-transparency leaves the agent guessing about what to expect.

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 a single sentence that is front-loaded with the core purpose. The trailing phrase about convergence picks is slightly ambiguous but does not add unnecessary length or waste.

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 one-parameter tool with no output schema, the description lists the key components of the thesis and gives a sense of scope. However, it omits how the response is structured, what 'top convergence picks' refers to, and any limitations, leaving gaps in completeness.

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 single 'ticker' parameter is fully documented in the schema (coverage 100%), so the baseline is appropriate. The description does not add any extra meaning or constraints to the parameter beyond what the schema already states.

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 uses a specific verb ('get') and resource ('thesis') scoped to a ticker, and enumerates the thesis components (quantitative read, catalysts, risks, bear case). This clearly differentiates it from sibling tools like get_ticker_signal or get_convergence_picks.

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 implies this tool is for a comprehensive, plain-language view of a ticker, but it does not explicitly state when to use it instead of siblings or provide alternative recommendations. The guidance is only implicit.

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