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anythink-cloud

Anythink-MCP

Official

Data: update

data_update
Destructive

Update an existing record by providing entity, record ID, and JSON fields; keeps Anythink-MCP backend data accurate without manual edits.

Instructions

Update a record

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesRecord ID
dataNoJSON object with fields to update
entityYesEntity name

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.27

TDQS

C2.2/5.0
Behavior2/5

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

Annotations already declare destructiveHint=true, readOnlyHint=false, and openWorldHint=false, so the safety profile is partially covered. The description adds nothing on top: it does not say whether unspecified fields are preserved or cleared, whether the entity must already exist, or what happens on an unknown id — all critical for a destructive mutation.

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

Conciseness2/5

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

Three words with zero waste, but this is under-specification rather than conciseness. Nothing is front-loaded because there is nothing to front-load; the description fails to earn its place by omitting anything actionable.

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?

For a destructive, non-classified mutation tool with no output schema, the description should at least state the replace-vs-merge behavior and failure modes. The annotations cover only the destructive flag, leaving the description materially incomplete for an agent deciding how to build the update payload.

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% (id, entity, data are all documented inline), so the baseline is 3. The description adds no meaning beyond the schema — it does not explain the entity namespace or the JSON field semantics of "data" — but the schema itself carries the parameter documentation adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Update a record" essentially restates the tool name and title (data_update / "Data: update") without adding scope, entity type, or any distinction from siblings like data_create, data_get, data_delete, or data_list. It is a verb+resource, but so generic that an agent cannot tell what a "record" is here or how this differs from entities_update or fields_update.

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?

There is no when-to-use guidance, no prerequisites, and no named alternative (e.g., entities_update vs data_update vs fields_update). The only implied usage is the generic CRUD inference that "update" means modify an existing record, which the name already conveyed.

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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