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VirtualFlyBrain

by org.virtualflybrain
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get_term_info

Get term info for a VFB or anatomy ontology entity (VFB_*, FBbt_*, etc.). THIS IS THE QUERY DISCOVERY TOOL: the response's "Queries" array lists the valid query_type values that run_query accepts for this entity. ALWAYS call get_term_info before run_query unless you already obtained the query_type from a previous get_term_info call in this conversation. Returns: SuperTypes (classification), Tags (data flags like has_image, has_neuron_connectivity), Queries (valid query_types for run_query), RelatedTools (other MCP tools applicable to this entity, with default_args ready to copy — e.g. get_hierarchy with subclass_of for cell types or part_of for nervous-system regions), Images (keyed by template brain ID), Publications, Synonyms. Supports batch — pass an array of IDs to fetch in parallel; batch results are returned as a JSON object keyed by ID. To build VFB browser URLs from the Images field: https://v2.virtualflybrain.org/org.geppetto.frontend/geppetto?id=&i=,, — id= sets the focus term and i= lists images for the 3D viewer (template ID must be first in i= to set the coordinate space).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesOne or more VFB IDs to look up
force_refreshNoBypass the response cache and recompute this result. Expensive — leave it unset on a first call. Set it ONLY to re-try a call that, earlier in this same conversation, returned a result that was clearly wrong, stale, or reported as failed. Never set it on more than one retry of the same call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / force_refresh
      Added value: +{
+  "description": "Bypass the response cache and recompute this result. Expensive — leave it unset on a first call. Set it ONLY to re-try a call that, earlier in this same conversation, returned a result that was clearly wrong, stale, or reported as failed. Never set it on more than one retry of the same call.",
+  "type": "boolean"
+}
  2. Changed3 schema fields changed
    • changedInput schema / properties / id / description
      Previous value: -"VFB ID (e.g., VFB_jrcv0i43)"New value: +"One or more VFB IDs to look up"
    • addedInput schema / properties / id / oneOf
      Added value: +[
+  {
+    "description": "A single VFB ID (e.g., VFB_jrcv0i43)",
+    "type": "string"
+  },
+  {
+    "description": "An array of VFB IDs to fetch in batch (e.g., [\"VFB_jrcv0i43\", \"VFB_00101567\"])",
+    "items": {
+      "type": "string"
+    },
+    "type": "array"
+  }
+]
    • removedInput schema / properties / id / type
      Removed value: -"string"
  3. First observed

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the response structure (SuperTypes, Tags, Queries, RelatedTools, Images, Publications, Synonyms), batch behavior (results keyed by ID), and even URL construction for the 3D viewer. It doesn't explicitly state read-only semantics or error behavior, but the 'get' verb and the detailed output description provide a strong behavioral picture.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is lengthy but every sentence earns its place: it covers the core purpose, the critical workflow (ALWAYS call first), batch behavior, return fields, related tools, and URL template. It is front-loaded with the purpose and the most actionable guidance, and the details are structured clearly.

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

Completeness5/5

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

Given the tool's central role in a multi-tool workflow and the absence of an output schema, the description is remarkably complete. It explains what the Queries field is for, how to use RelatedTools, how to interpret Images for building URLs, and that batch results are keyed by ID. It provides all necessary context for correct selection and invocation, even without an output schema.

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 the baseline is 3, but the description adds value beyond the schema by explaining the batch mode in detail (array of IDs returns a JSON object keyed by ID) and providing examples of ID formats. It also clarifies that the Queries field is what run_query accepts, which helps understand the tool's role. The force_refresh parameter is already well-explained in the schema, and the description reinforces it without redundancy.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource ('Get term info for a VFB or anatomy ontology entity') and immediately clarifies its role as 'THE QUERY DISCOVERY TOOL', which distinguishes it from siblings like run_query and get_hierarchy. It also mentions the ID patterns (VFB_*, FBbt_*) and the returned Queries array, leaving no ambiguity about what the tool does.

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

Usage Guidelines5/5

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

Explicit usage guidance is provided: 'ALWAYS call get_term_info before run_query unless you already obtained the query_type from a previous get_term_info call in this conversation.' It also explains the batch usage (pass an array of IDs) and when to use the force_refresh parameter (via schema, but the description reinforces the workflow). This clearly states when to use this tool and how it relates to run_query.

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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