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MCPg - Production-grade PostgreSQL MCP Server

Recommend PG search maintenance

recommend_pg_search_maintenance
Read-only

Walk pg_search BM25 indexes to detect missing key fields or field configurations, outputting actionable SQL statements for each finding.

Instructions

Walk every pg_search BM25 index and emit advisor findings. Rules currently surfaced: missing_key_field (CRITICAL — the key_field reloption is required by upstream; an index without it can't satisfy queries) and no_field_configs (WARNING — none of the six *_fields reloptions are set, so the index falls back to default tokenization for every indexed column). Each finding carries a ready-to-run suggested_action SQL statement. Returns an empty list when the extension is not installed. Also feeds the pg_search BM25 Indexes category in audit_database.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseNoOptional: target a configured secondary (read-only) database by name; omit for the primary. Call list_databases to see the configured ids.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond the readOnlyHint annotation, the description reveals that the tool returns an empty list when the extension is not installed and that each finding carries a ready-to-run suggested_action SQL statement. This adds valuable behavioral context.

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?

The description is concise (several sentences) but packed with essential information: purpose, rule details with severity, action format, edge case, and integration context. No superfluous content.

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 tool's narrow purpose and the presence of an output schema, the description covers all necessary aspects: what it does, what findings it produces, what each finding contains, and the edge case of missing extension. It is adequately complete.

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?

The schema description coverage is 100%, so the schema already documents the optional database parameter. The tool description adds no additional meaning beyond what the schema provides, justifying the baseline score of 3.

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?

The description clearly states the tool walks every pg_search BM25 index and emits advisor findings, listing specific rules and their severities. It distinguishes itself from siblings by focusing on pg_search index maintenance, with no other sibling having this exact purpose.

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?

The description implicitly conveys when to use the tool (to get maintenance advice for pg_search BM25 indexes) and mentions it feeds into audit_database. However, it does not explicitly state when not to use it or name alternative tools, so it lacks exclusion guidance.

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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