analyze_vacuum

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

With no annotations provided, the description carries full burden. It discloses what is checked but omits behavioral traits such as whether the tool modifies data (assumed read-only), required permissions, output format, or side effects. Identifying tables needing manual vacuum hints at output but lacks detail. This is minimal disclosure.

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?

Two concise sentences with zero wasted words. The first sentence states the core action, the second adds detail on checks and constraints. Information is front-loaded and easily parsed.

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?

For a diagnostic tool with 2 optional parameters and no output schema, the description provides the core purpose and checks but lacks details on output interpretation, prerequisites (e.g., database access), or how the results should guide action. It is adequate but not fully complete given the complexity of vacuum analysis.

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 description coverage is 100%; both parameters (schema, timeout_ms) have descriptions in the input schema. The description adds no further meaning beyond the schema, so baseline 3 is appropriate.

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's purpose: analyzing PostgreSQL VACUUM maintenance status. It specifies the exact checks performed (dead tuple ratios, vacuum staleness, autovacuum configuration, tables needing manual VACUUM) and includes the constraint 'PostgreSQL only,' which clearly distinguishes it from siblings like analyze_connections or analyze_indexes.

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 implies usage for checking vacuum status but does not explicitly state when to use this tool versus alternatives. It lacks exclusions or comparison with sibling tools. The constraint 'PostgreSQL only' gives some guidance, but no direct 'when-not-to-use' or alternative tool names are mentioned.

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