SqlAugur

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, repeatable operations. The description adds valuable context beyond this: it specifies the output format ('Markdown overview'), clarifies the scope ('overview' vs. detailed), and mentions filtering capabilities (implied via parameters). However, it doesn't disclose potential limitations like rate limits or authentication needs, which keeps it from a perfect score.

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 extremely concise and front-loaded: it starts with the core purpose, then immediately provides usage guidelines. Every sentence earns its place by clarifying scope and differentiating from siblings, with no wasted words or redundant information.

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 (8 parameters, read-only/idempotent annotations, no output schema), the description is largely complete. It covers purpose, output format, and sibling differentiation. However, it doesn't mention the return structure or potential errors, which could be helpful since there's no output schema. This minor gap prevents a perfect score.

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%, meaning all parameters are well-documented in the input schema itself. The description adds minimal parameter semantics beyond the schema—it implies filtering via 'includeSchemas' and 'excludeSchemas' but doesn't explain syntax or behavior further. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

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: 'Markdown overview of database schema: tables, columns, types, PKs, FKs, unique/check constraints, defaults.' It uses specific verbs ('get', 'overview') and resources ('database schema'), and explicitly distinguishes it from siblings by mentioning 'get_plantuml_diagram for visual ER output or describe_table for single-table detail.' This provides clear differentiation.

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 states when to use this tool versus alternatives: 'Use get_plantuml_diagram for visual ER output or describe_table for single-table detail.' This gives clear guidance on tool selection based on output format (Markdown vs. visual) and scope (overview vs. single-table detail), addressing sibling differentiation directly.

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