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search_terms

Search VFB terms. This is the search virtualflybrain.org itself runs — the same Solr query, the same ranking — so what comes back first here is what a user would see first on the site.

USE filter_types BY DEFAULT. Unfiltered searches mix scRNAseq artifacts and developmental stages in with the entity the user wants.

Common filter_types recipes:

  • Neuron classes: ["neuron", "class"]

  • Individual neurons with images: ["neuron", "has_image"]

  • Neurons with connectome data: ["neuron", "has_neuron_connectivity"]

  • Brain regions / neuropils: ["anatomy"]

  • Genes: ["gene"]

  • Driver lines / expression patterns: ["expression_pattern"]

  • Datasets: ["dataset"]

There are over 200 type names and they change as data is added, so do NOT guess them: call list_search_facets to see the current vocabulary (optionally filtered, e.g. contains="lineage"). Names are matched case- and separator-insensitively, and a name that does not exist is an error with suggestions rather than a silently empty result.

Deprecated terms are excluded by the search itself — you do not need exclude_types: ["deprecated"], and adding it is harmless but pointless.

Stage filtering: VFB covers adult, larval, and embryonic data, and many anatomical FBbt classes are stage-agnostic. Do NOT add "adult" or "larva" to filter_types by default — only add them when the user is explicit about a stage (e.g. "adult Kenyon cells", "larval mushroom body"). Default searches should leave stage out so stage-agnostic classes and all life stages are visible.

Useful flags:

  • unique=true (the default) → one row per term. Turn it OFF only when you need to see WHICH synonym matched; with unique=false a term appears once per matching synonym, so "Kenyon cell" can return the same ID several times.

  • minimize_results=true → top 10, essential fields only, for exploratory searches.

  • auto_fetch_term_info=true → if an exact label match is found, returns get_term_info in the same response.

  • boost_types=["has_image", "has_neuron_connectivity"] → float data-rich entities to the top of the list without excluding anything else.

  • demote_types=["expression_pattern_fragment"] → sink noisy types to the bottom of the list instead of removing them.

If the search returns no good matches, do NOT fall back to training-data answers — try alternative spellings, synonyms, broader terms, or different filter_types.

Multiple filter_types are ANDed (results must match ALL). Multiple exclude_types are ORed (any match excludes). boost_types and demote_types re-order without excluding; boost wins if a term matches both.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNoNumber of results to return (default 150, max 1000) - use smaller numbers for focused searches
queryYesSearch query (e.g., medulla)
startNoPagination start index (default 0) - use to get results beyond the first page
uniqueNoOne row per term (default true). Set false to get a row per matching synonym, which shows WHICH name matched at the cost of repeating IDs.
boost_typesNoFloat results matching these facets_annotation types to the top of the ranked list without excluding others
demote_typesNoSink results matching these facets_annotation types to the bottom of the ranked list without excluding them. Ignored for a type that also appears in boost_types.
filter_typesNoFilter results to only include items matching ALL of these facets_annotation types (AND logic). Use list_search_facets for valid names.
exclude_typesNoExclude results matching ANY of these facets_annotation types (OR logic). Deprecated terms are already excluded.
minimize_resultsNoWhen true, return at most 10 results with only the essential fields. For exact matches, return only the matching result.
auto_fetch_term_infoNoWhen true and an exact label match is found, automatically fetch and include term info in the response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • changedInput schema / properties / boost_types / description
      Previous value: -"Boost ranking of results matching these facets_annotation types without excluding others"New value: +"Float results matching these facets_annotation types to the top of the ranked list without excluding others"
    • addedInput schema / properties / demote_types
      Added value: +{
      +  "description": "Sink results matching these facets_annotation types to the bottom of the ranked list without excluding them. Ignored for a type that also appears in boost_types.",
      +  "items": {
      +    "type": "string"
      +  },
      +  "type": "array"
      +}
    • changedInput schema / properties / exclude_types / description
      Previous value: -"Exclude results matching ANY of these facets_annotation types (OR logic)"New value: +"Exclude results matching ANY of these facets_annotation types (OR logic). Deprecated terms are already excluded."
    • changedInput schema / properties / filter_types / description
      Previous value: -"Filter results to only include items matching ALL of these facets_annotation types (AND logic)"New value: +"Filter results to only include items matching ALL of these facets_annotation types (AND logic). Use list_search_facets for valid names."
    • changedInput schema / properties / minimize_results / description
      Previous value: -"When true, limit results to top 10 for initial searches and add truncation metadata. For exact matches, return only the matching result."New value: +"When true, return at most 10 results with only the essential fields. For exact matches, return only the matching result."
    • addedInput schema / properties / unique
      Added value: +{
      +  "default": true,
      +  "description": "One row per term (default true). Set false to get a row per matching synonym, which shows WHICH name matched at the cost of repeating IDs.",
      +  "type": "boolean"
      +}
  2. Changed4 schema fields changed
    • addedInput schema / properties / auto_fetch_term_info
      Added value: +{
      +  "default": false,
      +  "description": "When true and an exact label match is found, automatically fetch and include term info in the response.",
      +  "type": "boolean"
      +}
    • addedInput schema / properties / minimize_results
      Added value: +{
      +  "default": false,
      +  "description": "When true, limit results to top 10 for initial searches and add truncation metadata. For exact matches, return only the matching result.",
      +  "type": "boolean"
      +}
    • addedInput schema / properties / rows
      Added value: +{
      +  "default": 150,
      +  "description": "Number of results to return (default 150, max 1000) - use smaller numbers for focused searches",
      +  "maximum": 1000,
      +  "type": "number"
      +}
    • addedInput schema / properties / start
      Added value: +{
      +  "default": 0,
      +  "description": "Pagination start index (default 0) - use to get results beyond the first page",
      +  "type": "number"
      +}
  3. First observed

TDQS

A5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and delivers richly: it discloses that deprecated terms are pre-excluded, that filter_types are ANDed while exclude_types are ORed, that boost/demote re-order without excluding, and that unique=false repeats IDs per matching synonym. It also explains exact-match behavior for auto_fetch_term_info and error handling for unknown type names. This is exemplary transparency.

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 long but impeccably structured and front-loaded. It opens with the core purpose, then moves through defaults, recipes, constraints, and flags, with each sentence adding unique value. No redundancy or fluff exists; the density is justified by the tool's 10-parameter complexity and domain-specific semantics.

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 complexity, absence of annotations, and lack of output schema, this description is exceptionally complete. It covers usage defaults, parameter interactions, edge cases (deprecated, unknown types, no matches), and even contextualizes the tool within the larger VFB ecosystem. The only minor gap is lack of example invocations, but the explicit recipes and flag explanations render this unnecessary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema covers 100% of parameters, the description adds substantial semantic depth: it explains the AND/OR logic for filter/exclude types, when to disable unique, the trade-offs of minimize_results, and provides concrete recipes for boost_types/demote_types. It even clarifies that adding exclude_types:['deprecated'] is harmless but pointless. This far exceeds baseline schema coverage.

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 opens with a clear verb+resource ('Search VFB terms') and immediately distinguishes the tool from siblings by stating it uses the same Solr query and ranking as the VFB site itself. It contrasts with list_search_facets (vocabulary listing) and get_term_info (exact-match info fetch), making the tool's unique role explicit.

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?

The description provides explicit, actionable guidance: 'USE filter_types BY DEFAULT', common filter recipes, instructions to call list_search_facets rather than guessing type names, stage-filtering rules, and a clear fallback strategy (try alternatives, not training-data). This goes well beyond typical tool descriptions and directly supports correct agent selection and invocation.

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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