Taplio for LinkedIn

Get post

get_post

Read-onlyIdempotent

Fetch a single LinkedIn post by id — either a Taplio post id or the LinkedIn urn list_posts returns for a post published directly on LinkedIn, which resolves within the last 90 days only. A post has status scheduled, sending, or sent; drafts are separate (use get_draft).

Input Schema

Name	Required	Description	Default
`id`	Yes	The id of the post to fetch (from list_posts).

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

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/closed-world, so the description doesn't need to restate safety. It adds genuinely new behavioral facts: LinkedIn urn ids only resolve within the last 90 days, and a post's status is limited to scheduled/sending/sent.

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?

Two sentences, front-loaded with the core action, and each clause carries information (id formats, time limit, status set, sibling exclusion). The trailing status enumeration is slightly tangential to fetching but aids interpretation.

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?

With an output schema present and full parameter documentation, the description only needed to cover input formats, the recency constraint, and the boundary against drafts — all of which it does.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description goes further by defining that `id` accepts either a Taplio post id or a LinkedIn urn and constrains the urn case to a 90-day window — semantics the schema does not convey.

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 (fetch a single LinkedIn post by id) and immediately distinguishes the two id flavors it accepts. It also separates itself from the nearest lookalike, get_draft, in the same breath.

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?

Explicitly routes draft fetching to get_draft and tells the agent where the id comes from (list_posts). It doesn't say when to prefer get_post over list_posts when listing would suffice, but the primary alternative is named and excluded.

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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