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BACH-AI-Tools

Postgres MCP Pro

analyze_db_health

Checks PostgreSQL database health by analyzing indexes, connections, vacuum status, sequences, replication, buffer cache, and constraints to identify performance issues and maintenance needs.

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?

With no annotations provided, the description carries full burden for behavioral disclosure. It describes what health checks are available but doesn't mention whether this is a read-only operation, if it requires specific permissions, what the output format looks like, whether it's resource-intensive, or if there are rate limits. For a health analysis tool with zero annotation coverage, this leaves significant behavioral gaps.

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 appropriately sized and front-loaded with the core purpose. The bulleted list efficiently presents health check options, and the final sentence adds important usage context about optional specification and default behavior. Every sentence earns its place, though the bulleted format could be slightly more concise.

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 no annotations and no output schema, the description is incomplete for a health analysis tool. It doesn't explain what the tool returns (e.g., health scores, warnings, detailed reports), how results are structured, whether it provides actionable recommendations, or what authentication/authorization is required. The parameter information is adequate, but overall context is insufficient.

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%, so the schema already documents the single parameter with its default value and valid options. The description adds marginal value by explaining the comma-separated list option and providing more detailed explanations of what each health check does (e.g., 'checks for invalid, duplicate, and bloated indexes' for 'index'), but doesn't fundamentally enhance understanding beyond what the schema provides.

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 tool's purpose as analyzing database health and lists specific health check categories (index, connection, vacuum, etc.). It distinguishes from siblings like analyze_query_indexes by focusing on overall database health rather than query-specific analysis. However, it doesn't explicitly contrast with all siblings like execute_sql or list_schemas.

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 database health monitoring but doesn't explicitly state when to use this tool versus alternatives like analyze_query_indexes or get_top_queries. It mentions the default behavior ('all' checks) but provides no guidance on prerequisites, timing, or exclusion criteria relative to sibling tools.

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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