clmmin

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

With no annotations, the description bears the full burden. It explains the API endpoint, response structure (keys), and data format. However, it does not disclose potential behavioral traits such as rate limits, error handling, or data coverage. The description is adequate but not comprehensive.

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 structured with sections but is somewhat lengthy. The example and response keys add context but could be condensed. It is not overly verbose, but some lines (e.g., the repeated parameter explanations) could be streamlined without losing clarity.

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 no output schema, the description includes response keys and an example, which aids understanding. However, it lacks details on error conditions, date range validation, or station code availability. The tool is simple, but the description could be more complete for an agent to handle edge cases.

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?

Input schema covers 100% of parameters with descriptions. The description adds value by providing a request example and explaining response keys for both JSON and CSV formats. This goes beyond the schema, giving the agent contextual understanding of how parameters are used in practice.

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 it is for 'Daily Minimum Temperature (CLMMINT) API Request', which specifies the resource (daily minimum temperature). The name matches the function. However, it does not explicitly differentiate from siblings like 'clmmaxt' (likely max temperature), leaving some ambiguity for the AI agent.

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 parameter details and an example but offers no guidance on when to use this tool versus alternatives (e.g., clmmaxt for maximum temperature). It lacks explicit context for appropriate usage or exclusions, which is important given multiple temperature-related sibling tools.

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