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db_explain

Analyze SQL query execution plans to identify optimization opportunities for PostgreSQL, MySQL, and SQLite databases.

Instructions

Get query execution plan for optimization analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesDatabase type
queryYesSQL query to analyze
connectionNoConnection string
hostNoDatabase host
portNoPort number
databaseNoDatabase name
userNoUsername
passwordNoPassword
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves an execution plan for analysis, which implies a read-only, non-destructive operation, but doesn't clarify authentication needs, rate limits, output format, or potential side effects (e.g., whether the query is executed or just analyzed). This leaves significant gaps for a tool with 8 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Get query execution plan') and adds context ('for optimization analysis') without unnecessary details. Every word earns its place, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't address how to handle database connections (e.g., using connection string vs. host/port parameters), what the output looks like, or error conditions. For a tool with multiple connection options and no structured output, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with all parameters well-documented in the schema itself. The description adds no additional parameter semantics beyond implying the query is for analysis rather than execution. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('query execution plan'), and it adds context about the goal ('for optimization analysis'). However, it doesn't explicitly differentiate from sibling tools like db_query or db_schema, which are related but serve different purposes (executing queries vs. analyzing execution plans).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a database connection), exclusions, or comparisons to siblings like db_query (for running queries) or db_health (for database status). Usage is implied only through the purpose statement.

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

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