Taplio for LinkedIn

Schedule draft

schedule_draft

Idempotent

Schedule a LinkedIn post draft to be published automatically at a future time.

Input Schema

Name	Required	Description	Default
`id`	Yes	The id of the draft to schedule (from list_drafts).
`scheduled_for`	Yes	When to auto-publish, as an ISO 8601 datetime (e.g. 2026-06-10T14:30:00Z). Must be at least 2 minutes in the future.

Output Schema

Name	Required	Description
`id`	Yes
`url`	Yes
`media`	No	Media attached to this post, for posts published through Taplio and directly on LinkedIn. `url` is a durable copy hosted by Taplio. Can be empty while `media_type` reports an image, video or document, when Taplio does not hold a copy of that media yet or can no longer recover it. Text and article posts return an empty array.
`status`	Yes
`content`	Yes
`metrics`	No
`sent_at`	No
`created_at`	Yes
`media_type`	No	Format of the post. Absent when the format cannot be determined.
`scheduled_for`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 26, 2026

addedOutput schema / properties / media / items / properties / title

Added value: +{
+  "description": "Document title shown on LinkedIn. Only set for documents.",
+  "type": "string"
+}

First observedOct 15, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnly=false, destructive=false, idempotent=true, and openWorld=true, so the safety profile is covered. The description adds the meaningful behavioral fact that publishing happens automatically at a future time, but says nothing about what happens if a schedule already exists, failure behavior, or whether this replaces prior scheduling.

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?

A single sentence, front-loaded with the action and resource, with no filler. Every clause (LinkedIn, draft, auto-publish, future time) carries information.

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 two-param scheduling tool with full schema descriptions, an output schema, and annotations covering safety and idempotency, the description covers the essential behavior. Minor gap: no mention of interaction with existing schedules or of the unschedule/cancel counterpart.

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% and the schema itself is strong — id sourced from list_drafts, ISO 8601 format, and the 2-minute-future constraint. The description adds no parameter detail beyond the schema, so the baseline 3 applies.

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

Purpose4/5

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

States a specific verb (schedule) and resource (LinkedIn post draft) plus the effect (auto-publish at a future time). This implicitly distinguishes it from publish_draft (immediate) and unschedule, but the description never names those siblings explicitly.

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

Usage Guidelines3/5

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

Implied usage is clear from the verb — use this when you want deferred publishing rather than immediate publish_draft. But there is no explicit when/when-not guidance and no named alternative, so the agent must infer the routing.

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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