SheetsData MCP

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, indicating this is a safe, non-destructive operation with open-world data. The description adds valuable context beyond annotations by specifying what gets checked (absolute maximum ratings, recommended operating conditions) and the output format (PASS/FAIL/WARNING per parameter with margins), which helps the agent understand the tool's behavior and expected results.

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 with three sentences: purpose statement, operational details, and a concrete example. Every sentence adds value without redundancy, and it's front-loaded with the core functionality. The example is particularly helpful for illustrating usage without being verbose.

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 tool with 7 parameters, no output schema, and annotations covering safety and data scope, the description is mostly complete. It explains the tool's purpose, behavior, and provides an example. However, it doesn't detail the return structure beyond 'PASS/FAIL/WARNING per parameter with margins', which might leave ambiguity about the output format. Given the annotations and schema coverage, this is a minor gap.

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?

Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds minimal parameter semantics beyond the schema by mentioning 'design parameters' in general and providing an example with specific parameters (input_voltage, output_current, ambient_temp), but it doesn't explain parameter interactions or constraints not covered in the schema. Baseline 3 is appropriate given 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 specific action ('validate whether a component will work within your operating conditions') and the mechanism ('checks the datasheet's absolute maximum ratings and recommended operating conditions against your design parameters'). It distinguishes this tool from siblings like 'get_part_details' or 'read_datasheet' by focusing on validation against design parameters rather than information retrieval.

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 context for when to use this tool (to validate component compatibility with design parameters) and includes an example that illustrates typical usage. However, it doesn't explicitly state when NOT to use it or mention specific alternatives among the sibling tools, such as 'compare_parts' or 'find_alternative', which might be relevant for component selection.

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