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Orphnet

@orphnet/d1-eloquent-mcp

by Orphnet

run_generate

Diff your models against existing migrations to see schema changes. Dry-run prints added, dropped, or altered columns; set write=true to create a reconciling migration file.

Instructions

Diff models against the project's migrations (schema diff) and report what a reconciling migration would change. Dry-run by default: prints per-model added/dropped/type-changed columns and writes NOTHING. Pass write=true to emit migration file(s) into the project's migrations directory (review them, then run_migrate). Delegates to d1-eloquent generate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoCustom migration name (used when exactly one file is written).
modelNoLimit the diff to one model (class/file name, e.g. 'User'). Default: every model.
writeNoEmit reconciling migration file(s). Default false (dry-run diff only).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0-beta.2

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 full burden. It clearly states dry-run writes nothing and write=true emits migration files. It mentions delegation to d1-eloquent generate. It does not explicitly declare read-only versus destructive, but the behavior is described well. Would benefit from stating it does not alter the database directly.

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 sentences covering purpose, default behavior, write mode with next step, and technical delegation. Every sentence adds value, no fluff. Well-structured and front-loaded.

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?

Given no output schema, the description usefully mentions the output format (prints per-model added/dropped/type-changed columns). It covers the main usage flow. Missing details on error cases or prerequisites, but overall sufficient for a tool with 3 optional parameters.

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%, baseline 3. The description does not repeat parameter details or add significant new meaning beyond the schema. It provides context for the write parameter (default false, write mode), but the schema already covers that. No added depth for name or model.

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 diffs models against migrations and reports what a reconciling migration would change. It distinguishes itself from siblings like run_migrate and run_rollback by focusing on generating migration files, and explicitly mentions a fallback to run_migrate as a next step.

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 explicit guidance: dry-run by default, use write=true to emit files, review then run migrate. It does not explicitly state when not to use this tool, but the context from sibling names (run_migrate, run_rollback) implies the workflow. Minor improvement could add a when-not directive.

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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