datasetsSearch the Fort Worth Open Data catalog of open datasets by keyword. Returns each dataset's resource_id, name, description, category and update date — pass the resource_id to query/metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max datasets (1-100, default 20). | |
| query | No | Keyword to search dataset titles/descriptions (e.g. "budget", "crime", "health"). | |
| offset | No | Pagination offset. |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {
+ "query": "crime"
+ },
+ {
+ "limit": 10,
+ "offset": 0,
+ "query": "budget"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. Description adds context about the specific catalog (Fort Worth Open Data) and return fields, as well as a workflow hint. It does not contradict annotations and provides additional useful behavioral details.
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?
Two sentences, each serving a clear purpose: the first states the function and return, the second gives a workflow instruction. No redundant information; efficient and front-loaded.
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?
For a simple search tool with 3 parameters and no output schema, the description adequately lists return fields and hints at pagination (limit/offset). It also mentions the catalog source and next steps. Could mention case sensitivity or partial matching, but overall sufficient.
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 coverage is 100%, so description does not need to add parameter details. It mentions 'by keyword' aligning with query, but does not elaborate on limit or offset semantics beyond what schema already provides. No additional meaning added.
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?
Description clearly states 'Search the Fort Worth Open Data catalog of open datasets by keyword.' It specifies a verb (search), resource (Fort Worth Open Data catalog), and lists return fields. It also distinguishes from sibling tools by referencing 'query/metadata' as next steps.
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?
Description implies use for dataset discovery by keyword and instructs to pass resource_id to query/metadata. However, it does not explicitly state when to use or not use this tool versus siblings, nor does it list exclusions or alternatives directly.
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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