Search the indicative Lender Criteria Index by borrower scenario (e.g. 'self-employed', 'CCJ', 'contractor'). Returns how much of the market typically accepts it and a typical LTV band. Not a named lender's policy and not advice: speak to a regulated broker.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Words to match in the scenario, group or notes. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description does meaningful work by disclosing that results are indicative, return market acceptance and a typical LTV band, and must not be treated as lender policy or advice. It does not explain result ranking, matching behavior, or data freshness, so it falls short of fully 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?
The description is three tight sentences, front-loads the core function, and uses the remaining space for return behavior and a critical disclaimer. No sentence is redundant.
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 one-parameter search with no output schema, the description supplies enough context: the input scenario examples, the meaning of the output metrics, the indicative nature of the data, and the broker/advice boundary. Nothing essential for correct invocation is missing.
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 the schema already defines the query parameter; the description adds useful semantic examples of borrower scenarios beyond the schema text. It does not clarify what happens with an empty or optional query, leaving a small gap.
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 gives a specific verb and resource: searching the indicative Lender Criteria Index for borrower scenarios. The examples ('self-employed', 'CCJ', 'contractor') and the stated return values (market acceptance share and typical LTV band) make the tool's purpose unambiguous.
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?
It clearly indicates when to use the tool: borrower-scenario searches, with representative examples. It also warns that it is 'not a named lender's policy and not advice,' which sets an important boundary, though there is no explicit when-not-to-use guidance or alternative tool recommendation.
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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