get_scheduled_postFetch one scheduled post with approval, recurrence, retry, and published-link metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Compatibility alias for postId. | |
| postId | No | Scheduled post ID. | |
| team_id | No | Team ID to operate in team scope. Get available teams with list_teams. If omitted, uses personal scope. | |
| scheduleId | No | Compatibility alias for postId. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / anyOfRemoved value: -[
- {
- "required": [
- "postId"
- ]
- },
- {
- "required": [
- "scheduleId"
- ]
- },
- {
- "required": [
- "id"
- ]
- }
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this tool as read-only, idempotent, and non-destructive. The description adds the scope of returned metadata but does not disclose error behavior, required permissions, or what happens if the post is not found. It offers some additional context beyond annotations, but not rich behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It states the action, the resource, and the key metadata dimensions clearly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool, the description gives a high-level return summary but fails to mention that at least one identifier (id, postId, or scheduleId) is required, despite the schema marking all as optional. It also relies on the metadata categories to imply return structure, which is partially helpful but incomplete given the absence of an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for all four parameters, including clear descriptions and alias relationships. The tool description adds no parameter-specific information, but the schema already handles this well, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Fetch' and clearly states the resource: one scheduled post. It also enumerates the metadata categories (approval, recurrence, retry, published-link), and the singular 'one' differentiates it from the plural sibling get_scheduled_posts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a single scheduled post, but it does not explicitly contrast with get_scheduled_posts or mention when to use this tool instead of edit/delete/retry siblings. No alternative tools are named, leaving usage context implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
With 148 tools, there is significant overlap. For example, generate_content, publish_ai, generate_post_bundle, and request_project_content all generate content; get_analytics, get_unified_analytics, get_post_analytics, get_ad_performance, and get_unified_ad_report all fetch performance metrics; and list_inbox vs list_conversations blur comment and conversation management. Descriptions help, but boundaries between tools are often unclear.
Most tools follow a verb_noun pattern (e.g., list_teams, create_goal, delete_post), but there are notable deviations: create_library_item vs save_to_library, publish_content vs publish_ai, schedule_content vs schedule_content_advanced, and connect_platform vs connect_connector. Mixed prefixes like 'autopilot_', 'check_', and 'get_' are fine, but overlapping verbs and a hyphen in 'connect_linkedin-page' reduce consistency.
148 tools is extreme for any server. Even for a broad social media management platform, this is far beyond what an agent can effectively navigate. The count is unwieldy and suggests the surface should be split into multiple focused servers (publishing, analytics, connectors, workflows, etc.).
The core social publishing workflow is well covered (create, schedule, publish, edit, delete, retry), and there are extensive features for analytics, workflows, connectors, and AI agents. However, some resources have CRUD gaps: no update/delete for brand voices, no delete_project, no update/delete for Product Hunt goals, and no explicit get_workflow. These are workable but notable omissions.