Postgres MCP Pro

analyze_workload_indexes

Read-only

Analyzes frequent queries to recommend optimal indexes, improving database performance by reducing query execution time.

Instructions

Analyze frequently executed queries in the database and recommend optimal indexes

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "analyze_workload_indexes"
  }
}

Input Schema

Name	Required	Description	Default
`max_index_size_mb`	No	Max index size in MB
`method`	No	Method to use for analysis	dta

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Jun 23, 2026

TDQS

B3.3/5.0

Behavior3/5

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

The annotations already declare readOnlyHint=true, so the description's read-only analysis nature is consistent. It adds context that the analysis targets 'frequently executed queries' and produces index recommendations, but does not disclose any potential performance impact, the fact that it does not apply indexes, or what happens with the output beyond being a recommendation.

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 sentence that immediately states the tool's purpose without superfluous words. It is front-loaded with the action and object.

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

Completeness3/5

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

Given the presence of an output schema and full schema parameter coverage, the description is minimally sufficient. However, it lacks information on the two methods ('dta' vs 'llm') and does not clarify how this tool differs from the closely named sibling 'analyze_query_indexes', which is a notable gap for selection.

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?

Schema description coverage is 100%, with both 'method' and 'max_index_size_mb' having descriptions. The tool description adds no parameter-specific semantics beyond the schema, so it does not exceed the baseline.

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 uses a specific verb ('Analyze') and identifies the resource ('frequently executed queries') and outcome ('recommend optimal indexes'), making the tool's function clear. However, it does not explicitly differentiate from the sibling tool 'analyze_query_indexes', which may operate on a single query rather than a workload.

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 like 'analyze_query_indexes' or 'get_top_queries'. It does not mention scenarios, prerequisites, or exclusions, leaving the agent to infer usage from the name and 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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