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Search user by email

glpi_search_user_by_email
Read-onlyIdempotent

Find users by exact email address (returns the user items: id, login, real name, first name...).

Input Schema

NameRequiredDescriptionDefault
emailYesEmail address
rangeNoPagination range, e.g. 0-49
fieldsNoField set: 'essential' (default, trims internal GLPI fields) or 'all'
formatNoOutput format: 'json' (default) or 'markdown' (a table for listings, key/value lines for one item; returned in both the text and the structured result)

Output Schema

NameRequiredDescriptionDefault
dataNo
noteNoPagination hint: how to fetch the next page
countNoItems in this page
formatNo'markdown' when data holds the markdown rendering

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is fully covered. The description adds that the result is a collection of user items, which is mildly useful, but says nothing about matching semantics beyond exactness, permissions, or how large result sets behave.

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?

A single front-loaded sentence with no filler; the purpose and the return shape are both packed in. The trailing '(id, login, real name, first name...)' is slightly redundant given an output schema exists, but it costs almost nothing.

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 read-only search tool with full schema coverage, an output schema, and safety annotations, the description supplies what the structured data cannot: the exact-match matching rule. It does not address pagination via 'range', but the schema documents that, so the remaining gap is minor.

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 100%, so email, range, fields, and format are already documented in the schema; baseline is 3. The description does add one genuine semantic detail the schema lacks: matching is exact rather than fuzzy, which affects how callers construct the email value.

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 and resource plus the lookup key: 'Find users by exact email address'. This implicitly separates it from glpi_get_user (by id) and glpi_list_users (unfiltered), but it never names those siblings, so the differentiation is left 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 Guidelines3/5

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

The 'exact email address' qualifier implies the usage mode (you already have a full email and want the matching user, not a partial-match browse), which is more than nothing. However, there is no explicit when-to-use, when-not-to-use, or pointer to glpi_get_user / glpi_list_users as alternatives.

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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