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Make a change through the SKU.io API

api_write
Destructive

Creates or changes data through a SKU.io REST API endpoint (POST, PUT or PATCH; reference: https://developer.sku.io). Only reviewed endpoints that create records or edit fields can be called; search_api marks them callable. Deletes, voids, cancels and sends are unavailable. Returns {status, data} or a detailed error such as validation_failed. Needs "Allow changes" for the endpoint's area. dry_run validates without changing anything; idempotency_key makes a retry safe.

Input Schema

NameRequiredDescriptionDefault
bodyNoThe JSON request body.
dry_runNoWhen true, validate the body against the endpoint and return what would be called, without changing anything.
endpoint_idYesAn endpoint_id from search_api, e.g. "post.inventory-adjustments".
path_paramsNoValues for the endpoint_id's {placeholders}, e.g. {"id": 12}.
idempotency_keyNoOptional, at most 128 characters. Repeating a call with the same key returns the first result instead of writing twice.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations cover the safety profile (destructiveHint=true, readOnlyHint=false, idempotentHint=false), but the description adds meaningful context beyond them: the 'Allow changes' permission requirement, dry_run's validate-only behavior, the idempotency_key retry guarantee, and the return shape/time error format. It does not address side-effect scope or rate limits, so just short of top marks.

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?

Four dense sentences that are front-loaded with the core operation before constraints and parameters. Efficient overall, though the parameter clause at the end reads as a compressed list that could be structured more cleanly.

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 5-param, nested-body, mutating call with no output schema, the description covers return format, required permission, dry-run safety, and retry semantics. Completeness is strong; only exhaustive side-effect/error handling detail is absent.

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 coverage is 100%, so all five parameters are already documented in the schema. The description restates dry_run and idempotency_key semantics that largely duplicate the schema text, adding only minor framing; baseline 3 is appropriate.

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?

States a specific verb and resource ('Creates or changes data through a SKU.io REST API endpoint') with the HTTP methods enumerated. It clearly distinguishes itself from the read sibling (api_read) and ties operation to search_api as the discovery mechanism, so an agent can tell it apart without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly bounds usage: only reviewed endpoints that create records or edit fields are callable, deletes/voids/cancels/sends are unavailable, and search_api marks callable endpoints. This gives both when-to-use and when-not, plus a routing alternative.

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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