Bytebase: search tables

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

With no annotations provided, the description carries the burden of behavioral transparency. It states that the tool returns only names and row counts, which is a key behavioral trait that helps an agent know what to expect. It also mentions the scale of the database to justify its behavior. This goes beyond the schema definition and adds value.

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 (three sentences) and front-loaded with the core purpose, then provides usage guidance and return scope. Every sentence adds value 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 simplicity (3 params, no output schema), the description is sufficient. It covers usage context and the return format, and the schema covers parameters. It could mention response format details beyond names and row counts, but not necessary for a search 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?

The schema has 100% description coverage, so the baseline is 3. However, the description adds meaning to the 'pattern' parameter by clarifying it matches on table names first and then column names, and it explains the default limit behavior in context. This slight enhancement justifies a 4.

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 that this tool finds tables by name or column name within a database. It also distinguishes itself from dumping a schema and mentions the scale of production databases (~1000 tables), which sets specific expectations for its use.

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?

It explicitly says 'Prefer this over dumping a schema' and mentions the alternative bytebase_describe_table for columns, which provides clear guidance on when to use this tool versus alternatives. Although it doesn't list all possible exclusions, the key context is covered.

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