Company Industry Search
company_industrySearch loaded curated company profiles by industry, category, or description signals.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| industry | Yes | Industry query, for example technology. |
company_industrySearch loaded curated company profiles by industry, category, or description signals.
| Name | Required | Description | Default |
|---|---|---|---|
| industry | Yes | Industry query, for example technology. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds 'loaded curated' and the ability to match on category or description signals, but it does not disclose match semantics, result limits, or whether the query is exact or fuzzy. With annotations present, this is adequate but not deeply transparent.
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?
A single sentence, front-loaded with the action and resource, and no filler. Every word contributes to understanding; the description is efficient for its scope.
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 one-parameter, read-only search tool, the description is mostly sufficient, but there is no output schema and no mention of what fields are returned or how results behave (e.g., fuzzy matching, pagination). It also leaves the choice between this and similar company search tools ambiguous.
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 already describes the sole parameter 'industry' with an example, and schema coverage is 100%. The description adds useful meaning by clarifying that the query applies across industry, category, or description signals, which the schema alone does not convey.
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 concrete operation ('Search') and a specific resource ('loaded curated company profiles'), and names the search dimensions (industry, category, description signals). This sufficiently conveys what the tool does, though it does not explicitly differentiate it from sibling tools like company_search or company_classify.
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?
There is no guidance on when to use this tool versus related siblings such as company_search, company_lookup_auto, or company_classify. The description implies a use case but leaves the selection logic entirely to inference, which is risky given the large sibling set.
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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