Get Table Statistics

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

Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds value by noting that the tool requires pg_stat_user_tables access and explaining that row counts come from autovacuum/analyze statistics rather than exact counts. No contradiction with annotations.

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

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

The description is well-structured with Args and Returns sections, but it is slightly verbose by repeating some schema details. It could be more concise while retaining all essential information. Still, it is clear and front-loaded.

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

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

The tool has no output schema, but the description details the return format (JSON or Markdown) and key fields. Important notes about row count accuracy and required privileges are included. For a read-only tool with three optional parameters, this is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and each parameter has a description. The description adds minor context (shows all user schemas if omitted) but does not significantly enhance beyond the schema. Baseline 3 is appropriate as the schema already carries the burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves detailed table statistics (size, rows, vacuum/analyze info, scan counts). It distinguishes itself from sibling tools like pg_count_rows (exact counts) and pg_bloat_report (bloat-specific), making its unique purpose evident.

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

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

The description explicitly lists use cases: identifying bloated tables, missing vacuums, or underused indexes. It also advises when to use an alternative (pg_count_rows for exact counts), providing clear guidance on when to use this tool vs. others.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.