Walk the knowledge graph around an entity: teachers and students (STUDIED_UNDER), exhibition participation, museum holdings (HELD_BY), memberships, awards. entity_type ∈ artist|work|exhibition|organization. Every edge carries its source citation and the target's URL.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| entity_type | Yes | ||
| relation_type | No | Filter to one RelationType, e.g. STUDIED_UNDER, HELD_BY. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds useful behavioral detail: every edge carries its source citation and target URL. No contradictions.
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?
Two sentences that are front-loaded with purpose and examples, then add constraint info. No redundant words.
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?
Given no output schema, the description explains the purpose, parameters, and response format (edges with citation and URL). It could mention pagination or limits, but is fairly complete for a simple relation listing 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 coverage is 33% (only relation_type has a description). The description adds meaning by explaining entity_type values and listing possible relation types, but does not describe the slug parameter. This partially compensates for the low schema coverage.
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 clearly states it walks the knowledge graph around an entity, lists specific relation types (e.g., STUDIED_UNDER, HELD_BY) and entity types (artist, work, exhibition, organization). It distinguishes from sibling tools like get_artist which fetch single entities.
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 description explains when to use the tool (to explore connections from an entity) and gives concrete examples of relations. It does not explicitly state when not to use it or mention alternatives, but the usage context is well implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a unique entity or action (e.g., get_artist vs. search_artists, get_relations vs. get_stats). No two tools have overlapping purposes, so an agent can clearly distinguish them.
All tools follow a consistent verb_noun pattern: either get_<entity> or search_<entity>. No mixing of conventions like camelCase or different verbs.
12 tools is well-scoped for an archive server covering artists, exhibitions, works, organizations, marks, press, and graph relations. Each tool earns its place without redundancy.
The tool surface covers the main entities (artists, works, exhibitions, organizations) and provides search and retrieval for all key types. Additional tools like get_relations and get_timeline fill gaps for connected data and chronology, making the set feel complete for its domain.