list_indicators

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 mentions reading from a local .json file, which hints at a read-only operation without external calls, but does not specify permissions, error handling, or data format details. This leaves gaps in understanding the tool's behavior for a mutation-free context.

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 appropriately sized and front-loaded, with the core purpose stated first, followed by parameter and return details in a structured format. Every sentence adds value, though the 'Returns' section could be slightly more informative given the lack of output schema.

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 low complexity (1 parameter, no nested objects, no output schema) and no annotations, the description is minimally adequate. It covers the basic purpose and parameter semantics but lacks details on error cases, data structure, or integration with sibling tools, leaving room for improvement in completeness.

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 description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'dataset_id' corresponds to dataset IDs like 'IFS', 'DOT', etc., and clarifies it's used to read from a specific .json file. This compensates well for the low schema coverage, though it doesn't detail all possible dataset values or file locations.

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: 'Returns a list of indicators for the specified dataset' with the specific action 'read from the corresponding .json file in the local indicators directory.' It distinguishes from sibling tools like 'list_countries' by focusing on indicators rather than countries, though it doesn't explicitly differentiate from data-fetching siblings like 'fetch_ifs_data' beyond the resource type.

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 no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'list_countries' for listing other resources or data-fetching tools like 'fetch_ifs_data' for retrieving actual data. Usage is implied by the purpose but lacks explicit context or exclusions.

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