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Augmented-Nature

GeneOntology MCP Server

get_ontology_stats

Retrieve statistical data on Gene Ontology terms, including counts and recent updates, for specific ontologies or overall analysis.

Instructions

Get statistics about GO ontologies (term counts, recent updates)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ontologyNoSpecific ontology or "all" for overall stats

Implementation Reference

  • The handler function that executes the get_ontology_stats tool, returning hardcoded statistics about GO ontologies including term counts, root terms, and evidence codes.
    private async handleGetOntologyStats(args: any) {
      try {
        const stats = {
          ontology: args.ontology || 'all',
          last_updated: new Date().toISOString().split('T')[0],
          note: 'Statistics are approximate and may vary based on data access methods',
          sources: {
            quickgo: 'https://www.ebi.ac.uk/QuickGO/',
            go_consortium: 'https://geneontology.org/',
            amigo: 'http://amigo.geneontology.org/'
          },
          approximate_counts: {
            molecular_function: {
              description: 'Molecular activities of gene products',
              estimated_terms: '~11,000',
              root_term: 'GO:0003674'
            },
            biological_process: {
              description: 'Larger processes accomplished by multiple molecular activities',
              estimated_terms: '~30,000',
              root_term: 'GO:0008150'
            },
            cellular_component: {
              description: 'Locations relative to cellular structures',
              estimated_terms: '~4,000',
              root_term: 'GO:0005575'
            }
          },
          evidence_codes: {
            experimental: ['EXP', 'IDA', 'IPI', 'IMP', 'IGI', 'IEP'],
            high_throughput: ['HTP', 'HDA', 'HMP', 'HGI', 'HEP'],
            computational: ['IBA', 'IBD', 'IKR', 'IRD', 'ISS', 'ISO', 'ISA', 'ISM', 'IGC', 'RCA'],
            author_statement: ['TAS', 'NAS'],
            curator_statement: ['IC', 'ND'],
            electronic: ['IEA']
          }
        };
    
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(stats, null, 2),
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: 'text',
              text: `Error getting ontology stats: ${error instanceof Error ? error.message : 'Unknown error'}`,
            },
          ],
          isError: true,
        };
      }
    }
  • Input schema definition for the get_ontology_stats tool, specifying optional 'ontology' parameter.
    {
      name: 'get_ontology_stats',
      description: 'Get statistics about GO ontologies (term counts, recent updates)',
      inputSchema: {
        type: 'object',
        properties: {
          ontology: { type: 'string', description: 'Specific ontology or "all" for overall stats' },
        },
        required: [],
      },
    },
  • src/index.ts:349-350 (registration)
    Registration in the tool request handler switch statement that dispatches to the handleGetOntologyStats method.
    case 'get_ontology_stats':
      return this.handleGetOntologyStats(args);
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but lacks critical behavioral details: it doesn't specify if this is a read-only operation (implied but not stated), what format the statistics are returned in, whether there are rate limits, authentication requirements, or how 'recent updates' are defined. For a tool with zero annotation coverage, this is a significant gap in 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 a single, efficient sentence that front-loads the core purpose ('Get statistics about GO ontologies') and provides specific examples in parentheses. There's zero wasted text, and it's appropriately sized for a simple tool with one parameter. Every word earns its place.

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

Completeness2/5

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

Given the tool's simplicity (1 optional parameter, no output schema, no annotations), the description is incomplete. It lacks information on return format, error handling, or behavioral constraints. While the purpose is clear, the absence of annotations and output schema means the description should provide more context about what the tool returns and how it behaves, which it doesn't do adequately.

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 input schema has 100% description coverage, with the single parameter 'ontology' fully documented in the schema. The description adds no additional parameter semantics beyond what's in the schema—it doesn't elaborate on ontology options, default behavior when parameter is omitted, or examples. With high schema coverage, the baseline is 3, and the description doesn't compensate with extra value.

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

Purpose4/5

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

The description clearly states the action ('Get statistics') and resource ('GO ontologies'), with specific examples of what statistics are retrieved ('term counts, recent updates'). It distinguishes from sibling tools like get_go_term (which retrieves a single term) and search_go_terms (which searches terms), but doesn't explicitly differentiate from validate_go_id. The purpose is specific and actionable.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer this over get_go_term for statistical overviews versus detailed term data, or how it relates to search_go_terms for broader queries. There's no context about prerequisites, timing, or exclusions, leaving usage entirely implicit.

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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