Toolstem MCP Server

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 mentions the return format ('curated list with derived signals') and categories like cap_category, which adds value. However, it lacks details on potential limitations (e.g., data freshness, rate limits, authentication needs, or error handling), which are important for a tool with 16 parameters and no annotated safety profile.

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 efficiently structured in two sentences: the first explains the tool's function and output, and the second provides usage examples. Every phrase adds value without redundancy, making it easy for an agent to parse and understand the tool's purpose quickly.

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 (16 parameters, no annotations, but with an output schema), the description is reasonably complete. It covers the purpose, output signals, and usage contexts. However, it could improve by addressing behavioral aspects like data sources or limitations, especially since annotations are absent. The presence of an output schema reduces the need to detail return values, but more operational transparency would enhance 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 schema description coverage is 100%, so the schema already documents all 16 parameters thoroughly. The description lists some filtering criteria (e.g., 'sector, market cap, price range') but does not add significant semantic context beyond what the schema provides, such as explaining interdependencies or typical use cases for specific parameters. This meets the baseline 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 verb ('screen and filter') and resource ('stocks'), lists specific filtering criteria (sector, market cap, etc.), and explains the output ('curated list with derived signals'). It distinguishes itself from sibling tools like 'get_stock_snapshot' or 'get_company_metrics' by focusing on multi-criteria filtering rather than single-entity retrieval or comparison.

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 clear usage contexts ('discover stocks matching specific investment criteria, build watchlists, or find opportunities within a sector'), which helps an agent understand when to invoke this tool. However, it does not explicitly state when NOT to use it or mention alternatives among sibling tools (e.g., 'compare_companies' for direct comparisons), leaving some ambiguity in tool selection.

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