explain_query

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

With no annotations, the description reveals database-dependent behavior (different EXPLAIN commands) and that it returns plain-English recommendations. It does not state if it modifies data or requires permissions, but the core behavior is well disclosed.

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?

Two sentences with zero wasted words. Key information is front-loaded. The '[BUILD tier]' note adds context without clutter.

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 moderate complexity and no output schema, the description adequately covers purpose and output (plain-English recommendations). However, it omits input structure and whether a connection is required, slightly reducing completeness.

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 has no parameters, leaving the object content ambiguous. The description mentions analyzing a 'SQL query' but fails to clarify how the query is provided or if other fields (e.g., connection) are needed. Baseline for zero params is 4, but this gap reduces the score.

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 it analyzes a SQL query's execution plan and returns plain-English performance recommendations. It specifies database-specific EXPLAIN commands (Postgres vs MySQL), distinguishing it from sibling tools like 'optimize_query'.

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 implies usage for query analysis with mention of database types but lacks explicit when-to-use or when-not-to-use guidance compared to alternatives. No prerequisites or constraints are mentioned.

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