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get_most_frequent_queries

Retrieve the most frequently executed queries from Couchbase's completed_requests catalog to identify common usage patterns and optimize database performance.

Instructions

Get the N most frequent queries from the system:completed_requests catalog.

Args:
    limit: Number of queries to return (default: 10)

Returns:
    List of queries with their frequency count

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The primary handler function for the 'get_most_frequent_queries' tool. It executes a SQL++ query on system:completed_requests to find the most frequent user queries, excluding system and DDL queries, and handles empty results gracefully.
    def get_most_frequent_queries(ctx: Context, limit: int = 10) -> list[dict[str, Any]]:
        """Get the N most frequent queries from the system:completed_requests catalog.
    
        Args:
            limit: Number of queries to return (default: 10)
    
        Returns:
            List of queries with their frequency count
        """
        query = """
        SELECT statement,
            COUNT(1) AS queries
        FROM system:completed_requests
        WHERE UPPER(statement) NOT LIKE 'INFER %'
            AND UPPER(statement) NOT LIKE 'CREATE INDEX%'
            AND UPPER(statement) NOT LIKE 'CREATE PRIMARY INDEX%'
            AND UPPER(statement) NOT LIKE 'EXPLAIN %'
            AND UPPER(statement) NOT LIKE 'ADVISE %'
            AND UPPER(statement) NOT LIKE '% SYSTEM:%'
        GROUP BY statement
        LETTING queries = COUNT(1)
        ORDER BY queries DESC
        LIMIT $limit
        """
    
        return _run_query_tool_with_empty_message(
            ctx,
            query,
            limit=limit,
            empty_message=(
                "No completed queries were available to calculate most frequent queries."
            ),
        )
  • Helper utility function used by get_most_frequent_queries (and other query analysis tools) to run cluster-level queries and provide a standardized empty result message.
    def _run_query_tool_with_empty_message(
        ctx: Context,
        query: str,
        *,
        limit: int,
        empty_message: str,
        extra_payload: dict[str, Any] | None = None,
        **query_kwargs: Any,
    ) -> list[dict[str, Any]]:
        """Execute a cluster query with a consistent empty-result response."""
        results = run_cluster_query(ctx, query, limit=limit, **query_kwargs)
    
        if results:
            return results
    
        payload: dict[str, Any] = {"message": empty_message, "results": []}
        if extra_payload:
            payload.update(extra_payload)
        return [payload]
  • Registration of the get_most_frequent_queries tool in the ALL_TOOLS list, which is used to register all MCP tools with the server.
    ALL_TOOLS = [
        get_buckets_in_cluster,
        get_server_configuration_status,
        test_cluster_connection,
        get_scopes_and_collections_in_bucket,
        get_collections_in_scope,
        get_scopes_in_bucket,
        get_document_by_id,
        upsert_document_by_id,
        delete_document_by_id,
        get_schema_for_collection,
        run_sql_plus_plus_query,
        get_index_advisor_recommendations,
        list_indexes,
        get_cluster_health_and_services,
        get_queries_not_selective,
        get_queries_not_using_covering_index,
        get_queries_using_primary_index,
        get_queries_with_large_result_count,
        get_queries_with_largest_response_sizes,
        get_longest_running_queries,
        get_most_frequent_queries,
    ]
  • Import of the get_most_frequent_queries handler from the query module into the tools package.
    from .query import (
        get_longest_running_queries,
        get_most_frequent_queries,
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the action (retrieving frequent queries) and the return format (list with frequency counts), but lacks details on permissions, rate limits, or data freshness. It adds basic context but does not fully compensate for the absence of 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 front-loaded with the core purpose, followed by clear sections for arguments and returns. Every sentence is necessary and contributes to understanding, with no wasted words or redundancy.

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?

Given one parameter, no annotations, and an output schema (implied by 'Returns'), the description is mostly complete. It explains the tool's purpose, parameter, and return value, but could benefit from more behavioral context or usage guidance to fully compensate for the lack of annotations.

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?

The description adds meaning beyond the input schema by explaining that 'limit' controls the 'Number of queries to return' and specifying a default of 10. With 0% schema description coverage and only one parameter, this effectively compensates, though it could include more on constraints or effects.

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 clearly states the verb 'Get' and the resource 'N most frequent queries from the system:completed_requests catalog', making the purpose specific and actionable. It distinguishes from siblings like 'get_longest_running_queries' by focusing on frequency rather than duration or other query attributes.

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

Usage Guidelines3/5

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

The description implies usage for retrieving frequent queries from a specific catalog, but does not explicitly state when to use this tool versus alternatives like 'get_queries_with_largest_response_sizes' or 'get_longest_running_queries'. No exclusions or prerequisites are mentioned, leaving some ambiguity in context.

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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