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lu-query

lu-query

by zademy
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execute_dml_rollback_first

Dry-run an INSERT, UPDATE, DELETE, or MERGE in a rolled-back transaction to verify its validity and affected row count before applying it for real with execute_dml.

Instructions

Execute an INSERT, UPDATE, DELETE or MERGE inside a transaction that is immediately rolled back. Nothing is persisted; the tool only proves the statement is valid and reports the number of rows affected. Call execute_dml afterwards to apply the change for real.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "sql": "<sql>"
    },
    "name": "execute_dml_rollback_first"
  }
}

Input Schema

NameRequiredDescriptionDefault
sqlYesA single INSERT, UPDATE, DELETE or MERGE statement to dry-run (executed then rolled back).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.16.3

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that nothing is persisted, that the transaction rolls back, and that it reports rows affected, so the agent understands the side-effect profile. It omits permission/auth requirements and how the statement is validated, which keeps it short of a 5.

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?

Three tight sentences, front-loaded with the rollback semantics before the workflow instruction. Every sentence adds information (what runs, what persists, what to do next) with no redundancy.

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?

For a one-parameter tool with no output schema, the description supplies the missing return information ('reports the number of rows affected') and the non-persistence guarantee. Minor gaps remain around required privileges and the ambiguity versus execute_dml_preview, but the definition is essentially callable as written.

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% for the single `sql` parameter, so the schema already documents the accepted statement types. The description restates the same INSERT/UPDATE/DELETE/MERGE list and the dry-run behavior without adding syntax, size, or binding detail beyond the schema. Baseline 3 applies.

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?

States a specific verb (execute) and resource (INSERT/UPDATE/DELETE/MERGE) plus the key differentiator: the statement runs inside a transaction that is immediately rolled back. This clearly separates it from execute_dml and run_query without needing to open a schema.

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?

Explicitly states the workflow: validate here first, then 'Call execute_dml afterwards to apply the change for real.' This names the alternative tool and the condition that selects it. It does not, however, distinguish against the closely-named sibling execute_dml_preview, leaving one routing question open.

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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