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mysql_digest_top

Identify the top SQL statements causing wait time using performance_schema data, enabling focused performance troubleshooting without accessing application tables.

Instructions

Top statement digests by wait time from performance_schema (no application table reads).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the data source (performance_schema) and that it avoids application tables, which implies a read-only, non-intrusive operation. However, it does not explicitly state whether it modifies anything, how much data it returns, or any performance implications. The disclosure is partial, leaving some behavioral ambiguity.

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 that front-loads the core purpose ('Top statement digests by wait time') and immediately clarifies the source and exclusion. There is zero verbosity; every word contributes to the tool's semantics.

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

Completeness5/5

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

Given the tool has no parameters and an output schema exists, the description covers the essential context: what data it returns (top digests by wait time) and where it comes from (performance_schema). The explicit note about not reading application tables addresses a likely concern. Nothing critical is missing for an agent to call this tool correctly.

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

Parameters4/5

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

The tool has zero parameters, and the schema coverage is 100% (trivially). The baseline for 0 parameters is 4, and the description adds no parameter-specific information because none exists. This is appropriate; there is nothing for the description to explain.

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

Purpose5/5

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

The description clearly states the tool's function: it retrieves top statement digests ranked by wait time from performance_schema. It explicitly differentiates itself by noting 'no application table reads,' which distinguishes it from tools that might query application data. The verb+resource pattern is strong and unambiguous.

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

Usage Guidelines4/5

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

The description provides clear context: when you need top statement digests by wait time from performance_schema. It also signals a boundary by stating it avoids application table reads, which helps an agent avoid using it for app-data queries. However, it does not name any alternative tools explicitly, so the guidance is implied rather than explicit.

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