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cloudthinker-ai

Postgres MCP Pro Plus

analyze_schema_relationships

Analyze PostgreSQL schema relationships and dependencies with visual representation to understand database structure and connections.

Instructions

Analyze schema relationships and dependencies with visual representation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'visual representation', hinting at output format, but doesn't specify what that entails (e.g., graph, diagram, text), whether it's read-only or has side effects, or any performance or permission requirements. This leaves significant gaps for a tool with potential complexity in analysis.

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

Conciseness4/5

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

The description is a single, efficient sentence that directly states the tool's function. It's front-loaded with the core purpose and avoids unnecessary words, though it could be slightly more structured by elaborating on the 'visual representation' aspect to enhance clarity without losing conciseness.

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

Completeness3/5

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

Given the tool has 0 parameters and no output schema, the description is minimally complete but lacks depth. It hints at output ('visual representation') but doesn't detail what that means, and with no annotations, it fails to cover behavioral aspects like safety or performance. For an analysis tool, this leaves the agent with insufficient context to fully understand its use.

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

Parameters4/5

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

The tool has 0 parameters, with 100% schema description coverage, so there's no need to compensate for undocumented inputs. The description doesn't add parameter details beyond the schema, but with no parameters, a baseline of 4 is appropriate as it avoids confusion and aligns with the empty input structure.

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

Purpose4/5

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

The description clearly states the tool's purpose as 'Analyze schema relationships and dependencies with visual representation', specifying the verb 'analyze' and the resource 'schema relationships and dependencies'. It distinguishes from siblings like 'list_schemas' or 'get_object_details' by focusing on analysis rather than listing or retrieval, though it doesn't explicitly differentiate from other analysis tools like 'analyze_db_health'.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, and with siblings like 'list_schemas' and 'analyze_db_health', there's no indication of when this specific analysis tool is preferred over others for understanding schema structures.

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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