SheetsData MCP

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

Annotations already indicate it's read-only, non-destructive, and open-world, but the description adds valuable context: it explains the 'prefetch_datasheet' parameter's effect (triggering background extraction with no extra charge) and details the 'datasheet_status' field (e.g., 'ready', 'extracting'). This goes beyond annotations by clarifying behavioral aspects like cost and data availability.

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 front-loaded with the core purpose, followed by usage guidelines and parameter clarifications. Every sentence adds value—no wasted words—and it's structured logically from general to specific details, making it easy to parse 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 (fetching details from multiple providers) and lack of an output schema, the description does well by outlining what's returned (specs, pricing, stock, datasheet info) and behavioral notes. However, it could be more complete by explicitly mentioning potential limitations (e.g., provider availability or error cases), though annotations cover some aspects like open-world behavior.

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?

With 100% schema description coverage, the schema already documents all parameters well. The description adds some semantic context by emphasizing that 'part_number' must be a specific MPN or LCSC number (not values or descriptions), but it doesn't provide significant extra meaning beyond what's in the schema. 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 tool's purpose with specific verbs ('Get full details') and resources ('electronic component'), distinguishing it from siblings like 'search_parts' (which finds components) and 'read_datasheet' (which focuses on datasheets). It explicitly mentions what it returns (specs, pricing, stock, datasheet summary) and what it requires (MPN or LCSC number).

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 explicit guidance on when to use this tool ('Use after search_parts to drill into a specific result') and when not to use it (with examples of invalid inputs like '100nF' or 'buck converter'). It also distinguishes it from sibling tools by specifying its role in a workflow, making it clear when to choose this over alternatives.

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