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user_search

Read-only

Searches company employees by name, phone, email, department (role) and level; filters combine. Each employee comes with link (the name as a link) and mention (for a Kosmodrom chat message).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoPart of a first, last or middle name as written in the workspace; case-insensitive.
roleNoDepartment.
emailNoExact email, case-insensitive, e.g. to match an assignee from GitLab or another external system.
levelNoLevel or array of levels.
limitNoNumber of results (default 20, max 50).
phoneNoPhone number; formatting is ignored.
allowBlockedNoInclude employees with blocked access; default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

readOnlyHint=true already covers the safety profile, so the bar is lower. The description adds genuinely new behavioral context not present in annotations or schema: each result carries a link (name as hyperlink) and a mention (for Kosmodrom chat messages), which tells the agent how the output can be reused. It omits pagination/ordering behavior, so it stops short of 5.

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?

Two tight clauses with the filter list front-loaded and no filler. The second sentence on link/mention is slightly tangential but still earns its place by describing reusable output.

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

Completeness4/5

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

For a 7-parameter search tool with no output schema, the description covers the filter dimensions and the shape of returned employee objects (link, mention), which is what an agent needs to call and consume it. Missing details like result ordering or empty-result behavior are minor gaps.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3, but the description adds meaning beyond the schema: 'filters combine' discloses that the parameters are ANDed together, and 'department (role)' disambiguates the role enum as a department selector. These are real semantic additions the schema does not state.

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?

States a specific verb (Searches) and resource (company employees) plus the five filter dimensions, so the agent knows exactly what it retrieves. It does not differentiate itself from the sibling user_context, leaving the boundary between 'search users' and 'get user context' to inference.

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

Usage Guidelines2/5

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

The description gives no when-to-use or when-not guidance and never mentions the alternative user_context. It implies filter-based lookup but leaves selection between this and related user tools entirely unstated.

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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