build_key

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

With no annotations, the description carries the full burden. It discloses key behaviors: 'Unspecified dimensions are left empty (meaning "all values")' and 'constructs the key string with dimensions in the correct order according to the dataflow structure.' It also mentions the structured result. However, it does not disclose error handling or validation behavior (e.g., what happens if a dimension value is invalid), which would have made it fully transparent. Hence a 4 rather than 5.

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 a concise introduction, a key behavioral note, an explicit usage direction, and a formatted Args list. Every sentence adds value; there is no fluff or repetition. It is appropriately sized for a non-trivial helper tool.

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 role as a helper, the description covers its purpose, usage sequence relative to build_data_url, handling of unspecified dimensions, and return value. The output schema exists, so the description need not detail the return structure. It is suitably complete for an agent to invoke it correctly.

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?

Despite 0% schema description coverage, the description includes an Args section that richly explains each parameter: dataflow_id is 'the dataflow identifier', filters is 'Optional dict mapping dimension IDs to values', agency_id 'uses session endpoint if not specified', and endpoint is explained with examples ('FBOS', 'ECB') and defaulting behavior. This fully compensates for the schema's lack of descriptions.

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 'Build a properly formatted SDMX key from dimension values' and elaborates that it 'constructs the key string with dimensions in the correct order.' This specific verb+resource distinguishes it from sibling tools like build_data_url and validate_query, especially with the explicit 'Use this before build_data_url()' guidance.

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 explicitly tells the agent when to use it: 'Use this before build_data_url() to ensure your key has the correct format.' It also clarifies optional endpoint and agency overrides, providing clear context for when to employ the tool versus alternatives. This is strong usage guidance.

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