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danielldt

FrameIO MCP Server

by danielldt

generate_seed_data

Generate seed data scripts for development and testing by specifying module ID, entities, fields, and relationships. Create realistic test datasets with random, sequential, static, or faker-based values.

Instructions

Generate seed data scripts for development and testing

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entitiesYesEntity seed configurations
moduleIdYesModule ID (kebab-case)
tenantIdNoTenant ID for seed data (default: default)default

Schema Changelog

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

  1. First observedv1.0.0

TDQS

C2.9/5.0
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. It only states that the tool generates seed data scripts, giving no insight into side effects, return values, file output, or any behavioral nuances. For a complex tool with nested configurations, this is insufficient.

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 gets straight to the point. There is no wasted wording, and the core purpose is front-loaded. It earns full marks for efficiency.

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?

The tool has 3 parameters, including a complex nested structure for entities, and no output schema or annotations. The description provides no information about how the generated scripts behave, what the output looks like, or how relationships are handled. It is far too minimal for the complexity of the tool.

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%, meaning all parameters (moduleId, tenantId, entities) have descriptions in the schema itself. The description adds no extra parameter semantics, so a baseline of 3 is appropriate since the schema already documents them.

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 action (Generate) and the resource (seed data scripts) with a purpose (for development and testing). It is specific enough to distinguish from other generation tools, though it doesn't explicitly differentiate from siblings like generate_entity or generate_migration.

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?

No guidance is given on when to use this tool versus alternatives. There is no mention of when not to use it, prerequisites, or context in which it's appropriate. The tool name implies usage, but the description provides no explicit direction.

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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