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Schedule it MCP by usefulapi

Update resource

scheduleit_update_resource
DestructiveIdempotent

WRITE: change fields of an existing resource; only the fields you pass are changed. Passing group_ids replaces the whole list of groups; an empty string clears email or a detail field. POST /api/resources/{id}.

Input Schema

NameRequiredDescriptionDefault
nameNoResource name.
emailNoEmail address of the resource (an empty string clears it on update).
detailsNoDetail values keyed data1..data10 (for example data1 = job title; the labels are set in Schedule It). An empty string clears a field.
group_idsNoGroups the resource belongs to (the `owner` field). On update this REPLACES the whole list.
color_backNoResource background colour, e.g. #A9F5A9.
color_textNoResource text colour.
resource_idYesSchedule It resource id.
color_event_backNoBackground colour of this resource's events.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Adds real semantics beyond the annotations: selective field updates, list replacement for group_ids, and empty-string clearing of email/details. Annotations already flag destructiveHint and idempotentHint, so the description doesn't need to restate risk, but it could note that replacement of group_ids is the destructive path rather than leaving the agent to infer it.

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?

Three compact clauses with zero filler, front-loaded with the "WRITE:" marker that signals mutation first. Every clause carries distinct operational meaning.

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?

Covers the mutation model, clearing semantics and list-replacement hazard for an 8-parameter tool with a nested details object and no output schema. It leaves out error behavior (e.g. what happens with an unknown resource_id) and return shape, which the agent must assume.

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 the schema itself already documents the group_ids REPLACES behavior and the empty-string clearing rule, so the description mostly restates structured data. It adds a little emphasis on partial-update semantics but no new per-parameter detail (e.g. color pattern, details key range).

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?

Leads with an explicit operation class ("WRITE: change fields of an existing resource") naming both verb and resource, and the word "existing" cleanly separates it from the sibling create_resource. The endpoint reference (POST /api/resources/{id}) reinforces the target so an agent can distinguish it from update_event and update_group without opening a 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?

States the operative condition clearly: only the fields you pass are changed, so partial updates are safe. It does not name alternatives or exclusions (e.g. use create_resource for new resources, delete_event for removal), so routing still requires inference from the name.

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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