Get Jlcpcb Part

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds meaningful behavioral detail beyond these: the two backend modes (live API vs local DB), the fallback condition (API failure or missing credentials), the specific data returned (stock, tiered pricing, parameters, library type), and the 'source' field in the response. This is rich context that helps the agent predict behavior and interpret 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 concise and front-loaded. The first sentence states the core purpose, and the second paragraph details the credential-dependent behavior. Every sentence adds information, with no redundancy or off-topic content. Formatting with line breaks and quoting of env vars improves readability.

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 simple single-parameter nature, the presence of an output schema, and comprehensive annotations, the description is complete. It explains the important fallback behavior and the 'source' indicator, which is essential for the agent to interpret results correctly. There is no notable missing information for this tool's complexity.

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 input schema has 100% coverage for the single parameter with a clear description and examples ('LCSC part number (e.g., \'C25804\', \'C2286\')'). The tool description does not add additional parameter semantics beyond restating the purpose. This meets the baseline of 3 where the schema does the heavy lifting.

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 opens with a specific verb+resource: 'Get detailed information about a specific JLCPCB part by LCSC number.' This clearly distinguishes the tool from siblings like search_jlcpcb_parts (search vs get) and get_jlcpcb_database_stats (one part vs database-wide stats). The scope is unambiguous.

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 conditional context: if credentials are set, it performs a real-time lookup; otherwise or on failure, it falls back to the local snapshot. This is explicit when-to-use behavior. However, it does not explicitly name alternative tools (e.g., 'use search_jlcpcb_parts to find parts by query'), so it stops short of a 5.

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