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analyze_db_health

Read-only

Identify database health problems by running checks on indexes, connections, vacuum, sequences, replication, buffer cache, and constraints.

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

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already declare readOnlyHint=true. Description adds behavioral detail by listing each health check's purpose (e.g., 'checks for invalid, duplicate, and bloated indexes'), which is consistent with read-only analysis.

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?

Description is well-structured with a short opening sentence followed by bullet points listing checks. No wasted words, front-loaded with main purpose.

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

Completeness5/5

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

Given the single optional parameter and existing output schema, the description fully explains what the tool does, how to specify checks, and what each check covers.

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 coverage is 100% (one parameter fully described). Description adds minor nuance (comma-separated allowed) but does not significantly enhance understanding beyond the schema.

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?

Description clearly states 'Analyzes database health' and lists specific health checks (index, connection, vacuum, etc.), distinguishing it from sibling tools like analyze_query_indexes which focus on specific aspects.

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?

Provides clear guidance on how to use the tool: specify a single check or comma-separated list, default 'all'. However, does not explicitly compare to siblings or state when not to use this tool.

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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