get_field_values

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool retrieves 'most common values,' which implies a statistical or aggregated operation, but doesn't detail aspects like rate limits, authentication needs, error handling, or what 'most common' entails (e.g., based on frequency, time range). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 two sentences, front-loaded with the core purpose and followed by a concise usage hint. Every sentence earns its place by adding value: the first defines the action, and the second provides practical context. There is no redundancy or wasted words, making it highly efficient.

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 has no annotations, no output schema, and moderate complexity (3 parameters with 2 required), the description is partially complete. It covers the purpose and hints at usage but lacks details on behavior, return values, or error cases. For a discovery tool with full schema coverage, it's adequate but has clear gaps in transparency and output expectations.

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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by implying the tool is for 'discovering' values, which contextualizes the 'field' parameter. However, it doesn't provide additional semantics, examples, or constraints not covered in the schema descriptions. Baseline 3 is appropriate as 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 clearly states the tool's purpose: 'Get the most common values for a specific field.' It specifies the verb ('Get') and resource ('most common values for a specific field'), and provides concrete examples ('services, log levels, or other field values') that help distinguish it from siblings like 'search_logs' or 'get_sample_log'. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_mapping' might also retrieve field-related data).

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 context with 'Useful for discovering available services, log levels, or other field values,' suggesting it's for exploration or discovery rather than searching or filtering. However, it doesn't explicitly state when to use this tool versus alternatives like 'search_by_field' or 'get_sample_log', nor does it provide exclusions or prerequisites. The guidance is helpful but not comprehensive.

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