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get_post

Read-only

Get full details of a specific post including content, channels, media (with URLs), first comment, Instagram collaborators/user tags/location/Trial Reel state/Reel cover (thumbnail_type + thumb_offset in ms), dates, live URLs, per-platform publish errors, and retry linkage (retry_of / retries — a published post with empty published_urls and retries set is a resolved failure whose live URLs live on the retry post) — enough to fully verify a scheduled post without opening the dashboard. When a post has per-platform caption overrides (e.g. a shorter X version alongside the default), every variant is rendered as its own labeled block under ### Content so you can see exactly what each platform will publish. X threads are rendered under ### X Thread with each tweet labeled in publish order — read this to see the full chained tweet text, since thread-only posts have no caption in content. A LinkedIn poll is rendered under ### LinkedIn Profile Poll and/or ### LinkedIn Page Poll (independent per channel) with the question, options, and duration. After a post is published, published_urls maps each platform to the live post URL (only platforms that successfully posted appear).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe post ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, destructiveHint=false, openWorldHint=false), and the description goes further by disclosing return semantics: per-platform publish errors, how `retry_of`/`retries` indicate a resolved failure, and that `published_urls` only lists platforms that successfully posted. This is genuine behavioral context an agent cannot get from the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening clause is well front-loaded, but the body is one sprawling, unparagraphed run-on that mixes content rendering rules, thread handling, poll rendering, and retry semantics. The information is relevant, yet its density and lack of structure make it hard to scan for the one parameter an agent must supply.

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?

With no output schema, the description shoulders the return-value burden and does so thoroughly, covering content, media URLs, threads, polls, errors, and published URL mapping. It omits only edge behavior such as an invalid or missing post ID, which is a minor gap for a single-resource getter.

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 there is a single `id` parameter already documented as 'The post ID.' The description adds no format, source, or lookup guidance for the ID, so the baseline 3 applies – the schema carries the full burden.

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 and resource: 'Get full details of a specific post' with an enumerated scope (content, channels, media, errors, retry linkage). An agent can tell this is a single-post detail fetch, not a list or analytics call, though it never names the sibling it differs from (get_post_analytics, list_posts) to sharpen the distinction.

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?

Usage is only implied via the phrase 'enough to fully verify a scheduled post without opening the dashboard.' There is no explicit when-to-use, when-not-to-use, or named alternative such as get_post_analytics for metrics; the agent must infer the boundary itself.

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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