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it-romanov

Postgres MCP Pro

by it-romanov

analyze_db_health

Run health diagnostics on PostgreSQL: checks indexes, connections, vacuum, sequences, replication, buffers, and constraints. Identifies issues like bloat, wraparound risks, and poor cache hit rates.

Instructions

Analyzes database health. Here are the available health checks:

  • index - checks for invalid, duplicate, and bloated indexes

  • connection - checks the number of connection and their utilization

  • vacuum - checks vacuum health for transaction id wraparound

  • sequence - checks sequences at risk of exceeding their maximum value

  • replication - checks replication health including lag and slots

  • buffer - checks for buffer cache hit rates for indexes and tables

  • constraint - checks for invalid constraints

  • all - runs all checks You can optionally specify a single health check or a comma-separated list of health checks. The default is 'all' checks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
health_typeNoOptional. Valid values are: all, buffer, connection, constraint, index, replication, sequence, vacuum.all
Behavior2/5

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

No annotations are provided, and the description does not disclose whether the tool is read-only, requires special permissions, or has any side effects. It only describes the checks but lacks safety and behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose and uses a bulleted list for clarity. While slightly verbose, it is well-structured and each sentence provides value.

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?

For a tool with a single optional parameter and no output schema, the description adequately covers what the tool does and the available health checks. It could mention output format or prerequisites, but it's reasonably complete.

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 input schema has 100% coverage with a description listing valid values. The tool description adds significant meaning by explaining each health check option (index, connection, etc.), which goes beyond the schema's minimal description.

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 'Analyzes database health' and lists specific health checks, making the tool's purpose very explicit. It distinguishes itself from siblings like analyze_query_indexes by focusing on overall database health rather than specific query or index analysis.

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 clear guidance on how to use the optional health_type parameter, including default behavior and valid values. However, it does not explicitly contrast this tool with sibling tools or specify when to use it over alternatives.

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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