research_entities
Find regulator identifiers for institutions; names are not fuzzy-joined across regimes.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | ||
| limit | No | ||
| offset | No | ||
| dataset | Yes |
Find regulator identifiers for institutions; names are not fuzzy-joined across regimes.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | ||
| limit | No | ||
| offset | No | ||
| dataset | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, which cover safety. The description adds a specific behavioral trait—that name matching is not fuzzy across regimes—which goes beyond the annotations and informs the agent about exact-match semantics. This is valuable additional 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 a single sentence that front-loads the primary purpose ('Find regulator identifiers') and then adds the key caveat. It contains no filler or redundant content, achieving maximum efficiency.
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?
With four parameters (one required), no output schema, and no parameter descriptions, the description is far too sparse. It does not explain what 'dataset' refers to or how 'q', 'limit', and 'offset' behave. An agent cannot confidently construct a correct call without additional information.
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 0%, so the description must compensate for parameter meanings. It fails to explain any of the four parameters, including the required 'dataset' and the optional 'q', 'limit', and 'offset'. The description gives no clues about what these parameters control, leaving the agent to guess.
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 states a specific verb and resource: 'Find regulator identifiers for institutions.' This is clear and distinct from sibling tools like research_analysis or research_catalog, though it doesn't explicitly name any sibling. The caveat about fuzzy-joining adds specificity but doesn't directly differentiate from alternatives.
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 exact matching per regime ('names are not fuzzy-joined across regimes') but does not explicitly state when to use this tool versus research_tracked_institutions or other siblings. It provides a limitation but no direct usage guidance or alternative recommendations.
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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