get_personPerson affiliations, identifiers, project and section roles, credited items, publications, podcasts, videos and collaborators. Lists cap at 50 with totals. Use id to disambiguate.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Exact person Omeka id or typed id (person:123); required to disambiguate homonyms | |
| name | No | Full name in either order, with or without accents: 'Beier, Ulli' and 'Ulli Beier' both resolve |
Changes observed during successful MCP inspections.
Input schema / properties / idAdded value: +{
+ "anyOf": [
+ {
+ "exclusiveMinimum": 0,
+ "maximum": 9007199254740991,
+ "type": "integer"
+ },
+ {
+ "maxLength": 64,
+ "type": "string"
+ }
+ ],
+ "description": "Exact person Omeka id or typed id (person:123); required to disambiguate homonyms"
+}Input schema / properties / name / descriptionPrevious value: -"Either name order, with or without accents: 'Beier, Ulli' and 'Ulli Beier' both resolve"New value: +"Full name in either order, with or without accents: 'Beier, Ulli' and 'Ulli Beier' both resolve"Input schema / properties / name / maxLengthAdded value: +1000Input schema / requiredRemoved value: -[
- "name"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, so the safety profile is covered. The description adds a genuinely non-obvious behavioral trait beyond them: list sub-results are capped at 50 with totals reported, which tells the agent to expect truncated collections. It still omits whether a lookup miss errors or returns empty, but the cap disclosure is the kind of context annotations cannot carry.
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?
Three short sentences, no filler, and the disambiguation advice is placed last where it is actionable. The opening noun list is dense but front-loads the returnable content, which is useful given there is no output schema.
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 output schema, the description usefully substitutes by naming the categories of data returned, and it discloses the 50-item cap. What remains missing is failure behavior for ambiguous or unmatched names and any guidance on which sibling tool to use instead — modest gaps for a simple two-param read.
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%, so both params (id, name) are already fully documented including the homonym-disambiguation rule and accent/order tolerance for name. 'Use id to disambiguate' restates the schema's own wording, adding no new meaning. Baseline 3 applies when the schema does the heavy lifting.
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?
The description enumerates what the tool returns (affiliations, identifiers, roles, credited items, publications, podcasts, videos, collaborators) but never states the action plainly — it reads as a field list rather than 'retrieve a person's profile'. An agent can infer the purpose from name/title plus the field enumeration, but nothing distinguishes it from search_persons or resolve_entity beyond the read/write shape.
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?
The only usage guidance is 'Use id to disambiguate,' which is a parameter tip rather than when-to-use-this-vs-alternatives guidance. It never says when to prefer this over search_persons, resolve_entity, or get_entity_graph, nor what happens if only a name is supplied that matches multiple people.
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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