explore_schema

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It mentions the tool explores tables, columns, keys, indexes, and sample rows—implying a read-only nature. However, it does not disclose specific behaviors like sample row limits, whether all tables are listed when no table_name is given, or any performance implications for large schemas. Some transparency is present, but important details are missing.

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?

A single, concise sentence that front-loads the verb and resource list. No wasted words, no redundant information. It is efficient and immediately understandable.

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?

With no annotations, no output schema, and only a single parameter, the description must compensate for context. It lists what the tool explores but does not specify behavior when table_name is null (list all tables?) or provided (details for one table?), nor what 'sample rows' means (count? random? first N?). For a tool with moderate complexity and no other metadata, this is adequate but incomplete—more detail on parameters and behaviors would be expected.

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 input schema defines table_name as optional (string or null with default null), but the description does not explain its semantics—e.g., 'omit to list all tables' or 'specify to get details for a particular table.' Since schema coverage is limited (no descriptions in the schema), the description could have clarified how the parameter affects behavior. There is a general connection (the tool explores tables, so table_name likely filters by table), but this is only implied, not explicit.

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 uses a specific verb ('explore') with a clear resource list ('database tables, columns, keys, indexes, and sample rows'). This clearly communicates the tool's function and distinguishes it from sibling tools like query execution or explanation tools. It loses one point because it doesn't explicitly differentiate itself by naming any sibling tool or stating what it does NOT do (e.g., modifications, query execution).

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 conveys that this tool is for exploring schema structure, which implies usage for inspection rather than data manipulation. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'use get_schema for just columns' or 'don't use this for querying data'). No exclusions or alternative tool references are given, leaving the agent to infer context.

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