delete_scheduled_postCancel a scheduled post before it's published.
| Name | Required | Description | Default |
|---|---|---|---|
| team_id | No | Team ID to operate in team scope. Get available teams with list_teams. If omitted, uses personal scope. | |
| scheduleId | Yes | Schedule ID to delete |
| Name | Required | Description | Default |
|---|---|---|---|
| error | No | ||
| message | No | ||
| success | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "properties": {
+ "error": {
+ "type": "string"
+ },
+ "message": {
+ "type": "string"
+ },
+ "success": {
+ "type": "boolean"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already disclose destructiveHint=true and idempotentHint=true, so the description does not need to restate those. It adds the timing constraint ('before it's published') as useful context. However, it does not explain what happens after deletion (e.g., irreversibility, impact on related workflows), which is acceptable given the annotations but not comprehensive.
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, focused sentence that is front-loaded with the action and resource. Every word adds value, with no redundancy or filler.
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 tool with two parameters (one required), a clear output schema, and descriptive annotations, the description is sufficient. The timing constraint adds useful context, and the schema covers parameter details. It could be slightly more explicit about the state of the post after cancellation, but the overall picture is complete.
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 schema provides 100% coverage with descriptive text for both parameters (team_id and scheduleId), so the description adds no extra meaning beyond what's already structured. Baseline 3 is appropriate when the schema does the heavy lifting.
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 a specific verb ('cancel') and a specific resource ('scheduled post') with a clear timing qualifier ('before it's published'). This distinguishes it from sibling tools like delete_post (targets published posts) and edit_scheduled_post (modifies rather than cancels).
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 the tool is for scheduled posts that have not been published yet, providing clear context for when to use it. However, it does not explicitly name alternatives (e.g., edit_scheduled_post for changes, delete_post for published posts) or state when not to use it, so it falls short of the highest standard.
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.