Search Employee records by DisplayName (LIKE match).
Search Employee records by DisplayName (LIKE match).
| Name | Required | Description | Default |
|---|---|---|---|
| term | Yes | Search term matched against DisplayName with LIKE '%term%'. '%' is a wildcard; QBO does not support an ESCAPE clause. | |
| maxResults | No | Maximum number of results to return (default: 100, max: 1000) | |
| startPosition | No | Starting position for pagination (1-based, default: 1) |
Changes observed during successful MCP inspections.
v1.6.6Input schema / properties / term / descriptionPrevious value: -"Search term matched against DisplayName with LIKE '%term%'"New value: +"Search term matched against DisplayName with LIKE '%term%'. '%' is a wildcard; QBO does not support an ESCAPE clause."v1.5.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden, and it says almost nothing beyond the operation itself. It does not disclose result ordering, pagination/return behavior, or any caps on the match (the schema covers defaults but not behavior). Only the implicit read-only nature of a search partially fills the gap.
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 front-loaded sentence with zero filler — the operation and the match field appear immediately. It borders on under-specification rather than waste, but as written every word earns its place.
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?
With no annotations and no output schema, the description is the only prose layer, and it stops at the one-line summary. All three parameters are documented in the schema, but the agent still lacks sibling disambiguation (search vs. employees_list) and any return-shape or ordering context for this relatively simple search tool.
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 100%, and the schema already documents the LIKE semantics, wildcard handling, the absence of an ESCAPE clause, maxResults defaults/caps, and 1-based pagination. The description restates the LIKE match but adds no syntax, format, or interpretation detail beyond the schema, so the baseline of 3 applies.
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?
States a specific verb and resource ("Search Employee records") plus the matched field and match type (DisplayName, LIKE), so the operation itself is unambiguous. However, it never distinguishes itself from the sibling qbo_employees_list, which is the natural alternative when the agent wants all employees rather than a name-matched subset.
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?
Usage is only implied: the LIKE-on-DisplayName phrasing signals this is for partial-name lookups, and the required 'term' parameter reinforces that. There is no explicit when-to-use/when-not guidance and no pointer to qbo_employees_list for unfiltered retrieval, leaving the routing decision to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.