Search available CDC PLACES measures by name or category.
Returns matching measure IDs, names, and categories. Use this to find
the correct measure_id for other tools.
Categories: Health Outcomes, Health Behaviors, Prevention, Health Status.
Args:
keyword: Search term (e.g. 'diabetes', 'smoking', 'prevention', 'heart').
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that it returns matching measure IDs, names, and categories, and lists example categories. Since no annotations are provided, the description carries full burden and adequately covers the read-only search behavior without side effects.
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 very concise, using short sentences and bullet-like structure for categories. It front-loads the primary purpose and adds necessary details without redundancy.
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?
The tool is simple (1 param, search-only) and has an output schema (not provided but implied). The description covers what it does, what it returns, and why to use it, making it complete for typical usage.
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 single parameter 'keyword' is thoroughly described with examples (e.g., 'diabetes', 'smoking'). With 0% schema description coverage, the description fully compensates by adding meaning, usage tips, and examples.
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 searches CDC PLACES measures by name or category, returns specific fields (IDs, names, categories), and explicitly says it is used to find measure_id for other tools. This distinguishes it from sibling tools that operate on specific counties or tracts.
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 states to use this tool to find the correct measure_id for other tools, providing clear when-to-use guidance. However, it does not discuss when not to use it or directly compare to sibling tools, missing a bit of context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool serves a distinct purpose: comparing counties, retrieving county measures, getting a single measure across state, tract-level data, and searching measures. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (compare, get, get, get, search). Two tools are parallel (get_county_measures, get_tract_measures), and the others are clear and predictable.
Five tools cover the essential operations for a focused health dataset: retrieval at county and tract levels, comparison, state-level query, and metadata search. The count is well-scoped.
The set covers main use cases, but lacks a tool to retrieve all measures for all counties in a state at once. Users must either call per county or per measure, which is a minor gap.