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check_equivalence_preflight

Read-onlyIdempotent

Analyze SQL and view definitions preflight to identify semantic-equivalence proof risks, keeping raw definitions private.

Instructions

Analyze direct SQL and recursively resolved view definitions for semantic-equivalence proof risks without returning raw definitions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesRead-only SQL to inspect, including referenced view definitions.
database_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
headlineYes
functionsYes
risk_codesYes
analysis_scopeYes
classificationYes
contract_versionYes
coverage_completeYes
resolved_dependenciesYes
unresolved_dependenciesYes
direct_snapshot_supportedYes
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints. The description adds value by disclosing that it does not return raw definitions, only analysis, and notes recursive view resolution, which are behavioral traits beyond the annotations.

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, short sentence that conveys purpose, scope, and key behavioral constraint without unnecessary words. It is front-loaded and efficient.

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

Completeness4/5

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

With an output schema present, the description does not need to explain return values. It covers purpose and key behavior. However, it omits any guidance on the optional database_name parameter and does not mention when to use this over alternatives, leaving minor gaps for a tool with two parameters.

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

Parameters2/5

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

Schema coverage is 50% (sql described, database_name not). The description mentions 'direct SQL' and 'recursively resolved view definitions', which partly aligns with the sql parameter, but it does not clarify the role of database_name or provide any additional meaning for that parameter. The description largely repeats the schema's sql description.

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 uses specific verb 'Analyze' with clear objects 'direct SQL and recursively resolved view definitions' and states the goal 'semantic-equivalence proof risks'. It clearly distinguishes from sibling tools that compare results or plans, and the phrase 'without returning raw definitions' adds specificity.

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

Usage Guidelines3/5

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

The term 'preflight' implies use before an equivalence proof or transformation, but the description does not explicitly state when to use this tool versus alternatives like 'compare_query_results' or 'explain_query'. It provides clear context but no exclusions or alternative tools.

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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