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query_analyze_slow

Find performance bottlenecks in slow SQL queries by analyzing query structure and table schema, helping optimize database operations.

Instructions

Analyze slow database queries and identify performance bottlenecks

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe SQL query to analyze
api_keyNoAPI key for authentication
databaseNoDatabase enginepostgresql
table_infoNoTable schema info including existing indexes
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 does not state whether the query is actually executed on the database, whether the operation is read-only, what output is returned, or what the api_key is used for.

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 concise sentence with no filler. It front-loads the action and resource clearly, and every word contributes to understanding the tool's purpose.

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 that there is no output schema and no annotations, the description does not sufficiently explain expected return values, side effects, or prerequisites beyond parameter names. An agent would not know whether the tool executes the query, how results are presented, or whether api_key is required for every call.

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?

Schema description coverage is 100%, so the schema already documents all four parameters. The description adds no extra meaning about how parameters interact, what table_info should contain, or how database selection affects behavior, so it stays at the baseline.

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 analyzes slow database queries and identifies performance bottlenecks, providing a specific verb and resource. It does not explicitly differentiate itself from sibling tools like query_suggest_indexes or query_rewrite, so it misses the full 5.

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 gives no guidance on when to use this tool versus alternatives such as query_suggest_indexes, query_rewrite, or log_analyze. It implies usage context but never states exclusions or suitable scenarios.

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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