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CraveUp MCP Server

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by craveup

Archive (soft-delete) a location

delete_location
DestructiveIdempotent

Archive an unused duplicate location to free its slug and remove it from merchant lists while retaining order and menu data for audit.

Instructions

Soft-deletes a location: sets archivedAt, frees the slug, removes it from the merchant location list and Clerk org metadata. Order/menu rows remain for audit. Use to remove unused duplicates. Requires craveup login.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoPreview by default. Apply requires the exact returned planDigest.dry-run
locationIdYesCrave location id to archive
planDigestNoExact digest returned by a dry-run of the same arguments.
confirmationTokenNoRequired exact phrase for destructive, paid, or release operations.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
modeYes
statusYes
changesYes
summaryYes
operationYes
planDigestYes
environmentYes
nextActionsYes
schemaVersionYes
Install Server

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already include destructiveHint=true and readOnlyHint=false, and the description meaningfully elaborates beyond these: it specifies what is modified (archivedAt, slug, location list, Clerk org metadata) and what is preserved (order/menu rows for audit). It also discloses an authentication requirement. No contradiction with annotations exists.

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 three sentences with no filler. Each sentence earns its place: first states the operation and effects, second clarifies retention/audit behavior and use case, third gives an auth prerequisite. Information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is complete for this tool's complexity: it covers what the operation does, what remains intact, when to use it, and the login requirement. The input schema fully documents parameters, and an output schema exists, so return-value details are not required here.

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%, and every parameter already has a meaningful description, including dry-run/default behavior and the planDigest requirement. The tool description adds no extra parameter-level guidance, so the baseline score of 3 applies.

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 a specific verb ('Soft-deletes') and resource ('a location'), then enumerates concrete effects (sets archivedAt, frees the slug, removes from merchant location list and Clerk org metadata). It also differentiates this from a hard delete by noting order/menu rows remain for audit, distinguishing it from a sibling like delete_product.

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?

'Use to remove unused duplicates' gives an explicit intended use case, and 'Requires craveup login' adds an operational prerequisite. It does not explicitly name alternative tools or state when not to use it, but the purpose and context are clear enough for an agent to select it appropriately.

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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