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Ensembl

by io.github.pipeworx-io

Lookup Symbol

lookup_symbol
Read-onlyIdempotent

"What's the Ensembl ID for [gene symbol]" / "look up [gene] in Ensembl" / "BRCA1 / TP53 / BRAF Ensembl info" / "find gene [symbol] in [species]" — look up a gene by symbol within a species (e.g. species="human" symbol="BRCA1"). Returns Ensembl gene ID, chromosomal position, biotype, description. Use to convert HGNC gene symbols to Ensembl IDs for genomics workflows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expandNo
symbolYes
speciesYese.g. "human", "mus_musculus"
assemblyNoHuman genome build: "GRCh38" (the default) or "GRCh37" (= hg19). Coordinates you pass and coordinates you get back are both in this build. Older variant lists, spreadsheets and published tables are usually GRCh37.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoStable gene ID
endNoEnd coordinate
startNoStart coordinate
strandNoStrand
biotypeNoBiotype
speciesNoSpecies name
TranscriptNoTranscripts (if expand=true)
descriptionNoGene description
object_typeNoType of object
display_nameNoDisplay name
assembly_nameNoAssembly name
seq_region_nameNoChromosome

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / assembly
      Added value: +{
+  "description": "Human genome build: \"GRCh38\" (the default) or \"GRCh37\" (= hg19). Coordinates you pass and coordinates you get back are both in this build. Older variant lists, spreadsheets and published tables are usually GRCh37.",
+  "type": "string"
+}
  2. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "species": "human",
+    "symbol": "BRAF"
+  },
+  {
+    "expand": true,
+    "species": "mus_musculus",
+    "symbol": "Braf"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Gene lookup by symbol result",
+  "properties": {
+    "Transcript": {
+      "description": "Transcripts (if expand=true)",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "assembly_name": {
+      "description": "Assembly name",
+      "type": "string"
+    },
+    "biotype": {
+      "description": "Biotype",
+      "type": "string"
+    },
+    "description": {
+      "description": "Gene description",
+      "type": "string"
+    },
+    "display_name": {
+      "description": "Display name",
+      "type": "string"
+    },
+    "end": {
+      "description": "End coordinate",
+      "type": "integer"
+    },
+    "id": {
+      "description": "Stable gene ID",
+      "type": "string"
+    },
+    "object_type": {
+      "description": "Type of object",
+      "type": "string"
+    },
+    "seq_region_name": {
+      "description": "Chromosome",
+      "type": "string"
+    },
+    "species": {
+      "description": "Species name",
+      "type": "string"
+    },
+    "start": {
+      "description": "Start coordinate",
+      "type": "integer"
+    },
+    "strand": {
+      "description": "Strand",
+      "type": "integer"
+    }
+  },
+  "type": "object"
+}
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The annotations already signal readOnly, idempotent, openWorld, and non-destructive behavior, and the description does not contradict these. The description clearly indicates the tool returns gene information rather than performing mutations, so an agent can infer it has no side effects. It does not describe error behavior, but that is not required given the annotations.

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 compact and front-loaded, leading with the action and examples before listing returns and use case. It avoids unnecessary detail and every sentence adds useful context, with no redundant or filler content.

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?

The description names the return fields (Ensembl gene ID, chromosomal position, biotype, description) and the assembly coordinate behavior, which covers the main information an agent needs. It does not enumerate possible outputs or edge cases, but the absence of a full output schema is mitigated by the explicit list of returned fields.

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?

The schema descriptions cover species and assembly well, and symbol is inferable from the tool name and description. However, the 'expand' boolean parameter has no description in the schema or the main description, leaving its meaning ambiguous. With 50% schema description coverage and one entirely unexplained parameter, the description only partially compensates for the gap.

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 states a specific action ('look up a gene by symbol within a species'), includes concrete examples (BRCA1, TP53, BRAF), and lists the returned fields. It also identifies the intended use case, converting HGNC gene symbols to Ensembl IDs, making the tool's purpose unmistakable.

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

Usage Guidelines4/5

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

The description provides a clear when-to-use directive: 'Use to convert HGNC gene symbols to Ensembl IDs for genomics workflows.' It does not explicitly contrast with sibling tools such as lookup, sequence, or variation, but the stated use case is specific enough for an agent to select it appropriately in most situations.

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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TDQS

A3.6/5.0
Disambiguation2/5

There is heavy overlap in the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research, validate_claim) — several are near-identical 'route a natural-language question to a source' tools differing only by small qualifiers. ai_visibility_check vs scan_competitor_ai_presence and entity_profile vs compare_entities vs recent_changes also blur together. An agent could easily misselect among these.

Naming Consistency4/5

The dominant convention is snake_case verb_noun/noun_verb (list_subscriptions, scan_dependency, validate_claim, resolve_entity) which is fairly consistent, but there are several bare single-word verbs (lookup, sequence, variation, vep, xrefs, recall, remember, forget) that break the pattern. No camelCase is present, so the inconsistency is minor rather than chaotic.

Tool Count2/5

38 tools is heavy, and the overwhelming majority (~31) are Pipeworx meta-tools (subscriptions, memory, feedback, trend, discovery, llms.txt generation) that have nothing to do with the server's declared Ensembl identity. Only about 7 tools are actually genomics-related, so the count is inflated by off-domain additions that dilute the surface.

Completeness2/5

For the Ensembl domain, the surface covers gene lookup, symbol resolution, sequence retrieval, orthologs, SNPs, variant effect prediction, and xrefs — but misses major Ensembl capabilities like gene trees/families, regulatory features, comparative/multi-species alignments, expression data, phenotypes, GO/ontology annotations, and region/overlap queries. Conversely the Pipeworx tools are complete for their own domain but irrelevant here, leaving the declared domain notably incomplete.

Resources