colacloud-mcp

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 does well by describing the search functionality, pagination behavior (defaults and max), and return format. However, it doesn't mention important behavioral aspects like rate limits, authentication requirements, error conditions, or whether this is a read-only operation (though 'search' implies it likely is).

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 well-structured with clear sections (purpose explanation, Args, Returns) and every sentence adds value. The COLA explanation provides necessary domain context. While not minimal, the length is justified given the 10 parameters needing documentation. The information is front-loaded with the core purpose stated first.

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 search tool with 10 parameters, 0% schema coverage, no annotations, but with an output schema, the description does an excellent job. It explains the tool's purpose, documents all parameters thoroughly, describes the return format, and provides domain context about COLAs. The main gap is lack of explicit usage guidelines versus sibling tools.

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 0% schema description coverage and 10 parameters, the description fully compensates by providing detailed semantic explanations for every parameter. Each parameter gets clear documentation including search scope ('q: Full-text search query (searches brand, product name, origin)'), format examples ('YYYY-MM-DD'), constraints ('default: 20, max: 100'), and matching behavior ('partial match, case-insensitive').

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 as 'Search and filter COLA (Certificate of Label Approval) records,' providing a specific verb ('search and filter') and resource ('COLA records'). It distinguishes from siblings like 'get_cola' (which likely retrieves a single record) and 'search_permittees' (which searches different entities). The explanation of what COLAs are adds helpful domain context.

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 implies usage through the explanation of what COLAs are and the search/filter functionality, but doesn't explicitly state when to use this tool versus alternatives. No guidance is provided about when to use 'search_colas' versus 'get_cola' or 'search_permittees,' nor are there any prerequisites or exclusions mentioned.

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