search_local_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 effectively describes key behavioral traits: 'instant, offline' operation, 'no API call,' 'returns relevance-ranked matches,' and 'instant results.' It also clarifies what is NOT returned ('indicator codes but NOT database IDs'). However, it doesn't mention potential limitations like cache freshness or what happens with no matches.

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, how it works, search tips, examples, parameters, returns, note) and front-loads key information. While comprehensive, some sections like the example queries could be more concise. Every sentence adds value, but there's minor verbosity in the examples.

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 complexity (search functionality with behavioral nuances), no annotations, and an output schema (which handles return values), the description is remarkably complete. It covers purpose, usage guidelines, behavioral traits, parameter semantics, workflow integration with siblings, and practical examples, leaving no significant gaps for the agent.

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 schema description coverage is 0%, so the description must compensate. It provides meaningful context for both parameters: 'query' is explained with examples and search tips (e.g., 'simple keywords,' 'case-insensitive'), and 'limit' is clarified as 'maximum number of results to return' with the default value. This adds substantial value beyond the bare schema.

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: searching through locally cached metadata for World Bank indicators. It specifies the verb 'search' and resource 'local metadata for World Bank indicators,' and explicitly distinguishes it from the sibling 'search_datasets' tool by noting this is a 'FAST alternative' for discovering available data types before API search.

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 explicit guidance on when to use this tool versus alternatives. It states 'Use this to discover what types of data are available before using the API search' and names the specific alternative 'search_datasets.' It also includes a note explaining the workflow: after finding indicators here, use search_datasets to get database IDs for data retrieval.

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