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

With no annotations provided, the description carries the full burden of disclosing behavior. It mentions that the analysis costs 5 credits per call and is generated using Claude AI, which conveys cost and dynamic generation. It does not mention rate limits or side effects, but for a read-only analysis tool, the cost and AI-generated nature are the most important behavioral traits, adequately disclosed.

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 moderately sized, with the core purpose and usage front-loaded in the first two sentences. The subsequent list of return values and cost are each useful, but the description could be tightened slightly without losing information. Overall, it is well-structured and each sentence adds value.

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?

The description covers the tool's purpose, usage context, return content in detail, cost, and parameter requirement. Since there is no output schema, it appropriately lists the returned data types. It does not cover error cases or data freshness, but those are minor for this tool. The description is sufficiently complete for an agent to decide when and how to call it.

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 a detailed description of the 'ticker' parameter with examples, so coverage is 100%. The description only repeats that the parameter is required, adding no new meaning. This aligns with the baseline score of 3 for high schema coverage.

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's function: providing a comprehensive AI-generated stock analysis. It lists the specific outputs (fundamental data, technical indicators, AI assessment, rating, confidence score), which distinguishes it from sibling tools like get_prices or get_trading_signals that offer more limited data. This is a specific verb+resource with clear differentiation.

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: 'when you need detailed information about a company before making an investment decision.' It implies a use case of in-depth analysis rather than quick price checks, but it does not explicitly mention alternatives or when not to use it. This is clear context but lacks explicit exclusions, so it earns a 4.

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