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metricool_schedule_post

Schedule a LinkedIn post via Metricool with brand ID, text, and date/time. Returns the scheduled post ID and details.

Instructions

Schedule a LinkedIn post via Metricool. Returns the scheduled post ID and details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe post content (LinkedIn text post)
brandIdYesThe Metricool brand/account ID to post from
dateTimeYesScheduled date/time in ISO 8601 format (e.g., 2024-01-15T10:00:00)
imageUrlNoOptional URL to an image to include with the post
timezoneNoTimezone for the scheduled time (default: America/Costa_Rica)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that a scheduled post ID and details are returned, but says nothing about authentication/connection requirements, whether past dates are rejected, timezone handling behavior, or rate limits — significant gaps for a mutation tool.

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 short sentences with the core action front-loaded and no filler. It is appropriately sized, though the second sentence is minimal value given no output schema exists.

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

Completeness3/5

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

For a mutation tool with no annotations and no output schema, the description is minimally adequate — it states the action and that an ID/details are returned. It omits prerequisites and failure/edge-case behavior an agent would need to invoke it reliably.

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%, so the schema already documents all five parameters including the timezone default. The description adds no syntax, format, or constraint detail beyond what the schema provides, so the baseline 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?

States a specific verb ('Schedule') and resource ('LinkedIn post via Metricool'), naming both the platform and the scheduling nature. This clearly distinguishes it from the read-only siblings (get_brands, get_scheduled_posts, get_analytics, get_best_time).

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives, nor any prerequisites (e.g., needing a valid brandId from metricool_get_brands, or using get_best_time to pick a slot). Usage is only implied by the verb.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.