get_operator
Look up a Texas operator by RRC org number (exact) or name (fuzzy). One of org_no or name is required.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| state | No | TX | |
| org_no | No |
Look up a Texas operator by RRC org number (exact) or name (fuzzy). One of org_no or name is required.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| state | No | TX | |
| org_no | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It does mention the exact/fuzzy matching semantics and the required-parameter condition, which is useful. However, it omits critical behavioral details: what the response looks like, behavior when no match is found, handling of the state parameter, and the nature of the fuzzy matching. The agent is left without knowledge of return structure or error cases.
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 consists of two concise sentences that are front-loaded with the core action and required condition. Every word serves a purpose, with no fluff or repetition. It is appropriately sized for the tool's simplicity.
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 a lookup with 3 parameters, no annotations, and no output schema. The description covers the lookup mechanism but fails to state the return type, error behavior, or the role of the state parameter. This is a significant gap because the agent cannot predict what the tool will return or how failures are signaled, making the description incomplete for reliable invocation.
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. It clarifies that org_no is the RRC org number and that name uses fuzzy matching, and it specifies the OR requirement. However, the state parameter is entirely unmentioned, and its default value and purpose are not explained. The description adds value for two of three parameters but ignores the third.
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 function: 'Look up a Texas operator by RRC org number (exact) or name (fuzzy)'. It specifies a concrete verb ('look up'), resource ('Texas operator'), and the lookup methods (exact/fuzzy). This distinguishes it from siblings like search_operators by highlighting the exact-match capability and the specific identifier.
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 includes a usage constraint ('One of org_no or name is required') but offers no guidance on when to choose this tool over alternatives like search_operators. There is no mention of suitable scenarios, exclusions, or comparative context, leaving the agent to infer the tool's role from its name and siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource/action: datasets (list/download), counties (list), production (get by county), operators (exact lookup vs search). While get_operator and search_operators both deal with operators, the former is for exact/fuzzy single lookup while the latter is ranked FTS, making them distinguishable.
Tools follow a consistent verb_noun pattern (download_, get_, list_, search_) with clear prefixes. Although get_ and list_ both indicate retrieval, they apply to different resources and the verbs match the operation type (specific retrieval vs enumeration).
Six tools is well-scoped for a domain-specific data server, covering datasets, counties, production, and operators without redundancy.
The surface covers dataset discovery/download, county listing, production retrieval, and operator lookup/search—comprehensive for a data access API. No obvious missing CRUD operations since this is a read-only data source.