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daisydaines

fieldwork-mcp

by daisydaines

find_customer

Read-onlyIdempotent

Search Fieldwork customer records by name or other text to confirm whether a customer exists.

Instructions

Answer: "Do I have a customer named ___?", "Find customer Smith"

Search customers by name or other Fieldwork search text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds the domain-specific 'Fieldwork search text' but does not disclose additional behaviors such as matching logic, case sensitivity, or result limits, providing limited value beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded with examples, followed by a one-sentence definition. It avoids unnecessary verbosity, though the example-first structure is slightly unconventional. Every sentence contributes meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter search tool with an output schema and safety annotations, the description is mostly sufficient. The main gap is the lack of differentiation from the sibling 'search_customers' tool and no mention of the 'limit' parameter's behavior, which would be needed for full contextual completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% (no field descriptions), so the description must compensate. It clarifies that 'query' accepts a name or Fieldwork search text, adding meaning to that parameter. However, the 'limit' parameter is not addressed, leaving a gap in semantics for that field.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states it searches for customers by name or Fieldwork search text, with concrete example queries ('Do I have a customer named ___?', 'Find customer Smith'). The verb 'search' and resource 'customers' are clear, but it does not distinguish itself from the sibling 'search_customers' tool, so it lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The example questions provide clear context for when to use this tool—when you need to find a customer by name or a textual query. However, it does not mention when not to use it (e.g., for exact ID lookups via get_customer) or explicitly name alternatives, though the examples imply the typical usage.

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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