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create_schema

Create a new schema in Selise Blocks GraphQL API.

Args: schema_name: Name of the schema to create project_key: Project key (tenant ID). Uses global tenant_id if not provided

Returns: JSON string with schema creation result

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_keyNo
schema_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior2/5

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

There are no annotations, so the description must carry the behavioral transparency burden. It does disclose the return format ('JSON string with schema creation result') and the project_key fallback to global tenant_id, but it does not mention whether the schema requires later finalization (via finalize_schema), permissions needed, or other side effects. This is a significant gap given the existence of related siblings.

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 extremely concise: a single-sentence summary followed by a structured Args/Returns block. Every line contributes information, the main action is front-loaded, and there is no redundant or filler content.

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?

The tool is simple with only 2 parameters and an output schema, so the description doesn't need to explain return details. It covers the core purpose, all parameters, and the return format. However, it lacks lifecycle context (e.g., whether finalize_schema is required afterward) and usage guidance, which prevents it from being fully complete for agent decision-making.

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

Parameters5/5

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

Despite 0% schema description coverage, the description explicitly explains both parameters: schema_name as 'Name of the schema to create' and project_key as 'Project key (tenant ID). Uses global tenant_id if not provided'. This adds real meaning beyond the schema titles, including a default behavior, fully compensating for the schema's lack of descriptions.

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 first sentence clearly states the action and resource: 'Create a new schema in Selise Blocks GraphQL API.' This is a specific verb+resource statement that distinguishes it as a creation operation. However, it doesn't explicitly differentiate it from sibling tools like finalize_schema or update_schema_fields, so it falls short of a 5.

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 description implies the tool is for creating schemas, which is a clear context, but it offers no explicit guidance on when to use it versus alternatives or any prerequisites. No exclusion or alternative tool references are provided, so it meets the 'implied usage' level.

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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