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update_schema_fields

Update schema fields (step 2 of schema field management).

Args: schema_id: The ID of the schema to update fields: List of SchemaField objects for the schema (existing + new). Each SchemaField has Name (str), Type (str), and IsArray (bool) properties. Reserved fields (ItemId, CreatedDate, LastUpdatedDate, CreatedBy, Language, LastUpdatedBy, OrganizationIds, Tags) are automatically filtered out. project_key: Project key (tenant ID). Uses global tenant_id if not provided

Returns: JSON string with update result

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYes
schema_idYes
project_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.2/5.0
Behavior3/5

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 usefully discloses that reserved fields are automatically filtered out and that project_key falls back to the global tenant_id. However, it does not explain whether existing fields are replaced or merged, potential permissions, or error behavior, leaving gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear opening sentence and a formatted Args/Returns section. It is slightly lengthy due to listing all reserved fields, but each sentence adds meaningful detail without 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 3-parameter update tool with an output schema, the description is fairly complete: it covers all inputs, the return type, and key behavioral quirks. The main omission is the exact semantics of field replacement (e.g., whether unspecified fields are removed), which is important for a destructive-feeling update operation.

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?

The description provides thorough parameter explanations that go beyond the sparse input schema: it details the fields array with SchemaField properties, explains the project_key fallback, and lists the reserved field names. With 0% schema description coverage, this fully compensates.

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 updates schema fields, using the verb 'update' with a specific resource. The phrase 'step 2 of schema field management' provides context and distinguishes it from siblings like create_schema and get_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?

It indicates this is part of a multi-step schema field management process and describes the expected input (existing + new fields). However, it does not explicitly state when not to use this tool or directly name alternatives, leaving some ambiguity.

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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TDQS

A3.5/5.0
Disambiguation4/5

The tools are organized into clear domains (auth, roles, schemas, translations, projects), and within each domain, tools have distinct purposes (e.g., get_schema vs list_schemas, save_captcha_config vs update_captcha_status). A few pairs like get_auth_status and get_authentication_config could cause minor confusion, but their descriptions clarify the difference.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, using predictable verbs like get, list, create, update, set, enable, and configure. Even longer names like save_module_keys_with_translations adhere to the same convention, with no mixed casing or arbitrary styles.

Tool Count2/5

With 36 tools, the server exceeds the typical well-scoped range for MCP servers. While the broad platform domain justifies some breadth, the sheer volume can overwhelm agents and suggests the toolset could be consolidated or split into smaller, focused servers.

Completeness3/5

The toolset provides decent coverage for creation, listing, and some updates across entities like permissions, roles, schemas, and translations. However, there are notable gaps: no delete operations for most resources, no role update, and no project update/delete, which leaves lifecycle management incomplete.

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