industry_overviewFor one industry: ease tier (A–D), products that fit, lenders that serve or restrict it, SBA eligibility, specialty programs, the best first route, the dignity fallback when everything declines, and research white space.
| Name | Required | Description | Default |
|---|---|---|---|
| state | No | Two-letter US state code (e.g. NY). | |
| industry | Yes | Industry in a few words (e.g. "restaurants", "trucking", "dental practice"). No company names. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint in annotations, the description defines the expected qualitative output, such as providing ease tier classifications (A-D) and the 'dignity fallback.' This context is critical for an agent determining the depth of the report it is receiving.
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 concise and direct, functioning as an effective list of deliverables for the tool. It avoids fluff while effectively summarizing complex data fields.
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?
Given the holistic and complex nature of the report generated, the description is nearly exhaustive, providing a detailed map of all available information (e.g., SBA eligibility, white space) without requiring an output schema to be defined.
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?
Since the schema coverage is 100%, the baseline is 3. The description uses the parameters (industry, state) as context for the report rather than adding new semantic value beyond the input structure.
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 that the tool generates a comprehensive lending overview report for a single industry and defines all the specific data points contained within that report.
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 that this tool should be used when a broad, strategic market assessment is needed due to the wide range of data provided. However, it does not explicitly advise agents on when to prefer this over specific search-based siblings like find_lenders.
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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