Audit settings

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

The description comprehensively discloses behavior: it lists specific settings flagged, explains cross-setting comparisons, and details RAM-relative ratios with the caveat that PostgreSQL cannot see host RAM. This significantly adds context beyond the annotations (readOnlyHint, openWorldHint), accurately reflecting a non-destructive read audit.

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 concise yet packed with information, using clear formatting (backticks for settings, bullet-like listing, example call). Every sentence adds value, and the example at the end helps illustrate usage without redundancy.

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?

Given the tool's complexity (auditing multiple dimensions of PostgreSQL configuration), the description covers all key aspects: dangerous toggles, cross-setting issues, RAM analysis, and return format. The output schema exists, so detailed return description is not necessary. The example further clarifies usage, making the description fully complete for an AI agent.

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?

For the total_ram_mb parameter, the description adds critical meaning: 'when total_ram_mb is supplied — RAM-relative ratios for shared_buffers / effective_cache_size (PostgreSQL can't see host RAM itself).' This compensates for the schema lacking a description for that parameter. The database parameter is already well-described in the schema, so overall parameter clarity is excellent.

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 it performs a 'Sanity-sweep of postgresql.conf via pg_settings' and enumerates specific dangerous toggles, cross-setting issues, and RAM-relative analysis. It distinguishes from sibling tools like audit_database and audit_sequences by its focus on configuration settings rather than schema or data audits.

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 auditing PostgreSQL configuration, emphasizing it is a 'Pure read' operation. It provides context on when the total_ram_mb parameter is useful but does not explicitly state when not to use this tool or mention alternative tools for similar purposes.

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