search_tables

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

No annotations are provided, so the description bears full burden. It explains that the tool searches by pattern (substring match via example) but does not disclose details like case sensitivity, result limits, or behavior when no matches are found. The description is clear on usage but lacks comprehensive behavioral traits.

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 short and front-loaded with the critical usage note. It includes an emoji and all-caps emphasis, which are effective but slightly verbose. The example is useful. Overall, it communicates efficiently with minimal extra verbiage.

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 has 3 parameters, no output schema, and many siblings, the description covers the essential usage context. However, it lacks information about the return format (e.g., table names with schema details) and any limitations. This gap means the agent might not fully understand what to expect from the tool.

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 67% (pattern and database have descriptions, datasource_name does not). The description adds value through an example demonstrating pattern usage, but does not explain datasource_name or provide additional semantics beyond the schema. The baseline is 3 due to moderate schema coverage, and the description adds marginal value.

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: 'Search for tables by name pattern.' It uses a specific verb ('search') and resource ('tables'), and distinguishes from siblings like get_tables (which lists all tables) and validate_table_exists (checks existence). The critical note reinforces its unique role.

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 provides explicit when-to-use guidance: 'CRITICAL - USE FIRST when user mentions a table name' and 'NEVER assume table names exist - always search first.' It does not explicitly mention when-not-to-use or alternatives, but the priority instruction is strong and context from sibling tools implies alternatives.

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