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Glama

search_individuals

Read-onlyIdempotent

Find GEDCOM individuals by name, birth/death year range, place, or sex. Filter and rank matches by exact name first.

Instructions

Search individuals by name, birth/death year range, place or sex.

Matching is case- and accent-insensitive. Results are ranked: exact full-name matches first,
then surname/given matches, then partial matches; ties sort by surname then given name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sexNoM or F
fileNoGEDCOM file name (with or without .ged). Optional when only one file exists.
givenNoGiven-name filter (substring)
limitNo
placeNoMatches any event place, e.g. 'Bristol'
queryNoFree-text name match, e.g. 'john smith' or 'smith'
offsetNo
surnameNoSurname filter (substring)
birth_year_toNo
death_year_toNo
birth_year_fromNo
death_year_fromNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
offsetYes
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint=false), so the bar is lower. The description adds genuinely non-obvious behavior: matching is case- and accent-insensitive, and results are ranked by match quality with a specific tie-break order. It does not explain pagination interplay between limit/offset, but the ranking semantics are the more valuable disclosure.

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 sentences, front-loaded with the searchable fields before the matching/ranking rules. Every sentence carries information, though the ranking clause is dense and could be slightly tighter.

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?

An output schema exists, so return-value explanation is not needed. For a 12-parameter, zero-required search tool the description covers the semantically important filters and the ranking model; the missing pieces (file scoping, limit/offset behavior) are documented in the schema itself.

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 50%, the baseline for a 3. The description reinforces the meaning of query/given/surname, year ranges, place, and sex, and its note about accent-insensitive matching adds value beyond the raw schema strings. However, file, limit, and offset are left entirely to the schema, and the limit/offset interaction is never surfaced.

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 opens with a specific verb+resource ("Search individuals") and enumerates the searchable dimensions: name, birth/death year range, place, and sex. This clearly distinguishes it from point-lookup siblings like get_individual and get_family, though it never names those alternatives explicitly.

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?

Usage is implied by the tool name and the listed filters, but there is no explicit when-to-use/when-not-to-use guidance relative to siblings such as get_individual (exact lookup) or list_files. An agent must infer that this is the fuzzy/discovery entry point rather than one taking a known ID.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.