SendIt

Suggest Next Schedule Time

suggest_next_schedule_time

Read-onlyIdempotent

Suggest the next recommended publish time using best-times insights or configured queue slots without creating a post.

Input Schema

TableJSON Schema

Name	Required	Description
`mode`	No	Use 'best_time' for analytics-based suggestions or 'queue' for queue-slot suggestions.
`after`	No	Optional lower bound. Suggestions should be strictly after this time.
`team_id`	No	Team ID to operate in team scope. Get available teams with list_teams. If omitted, uses personal scope.
`platform`	No	Single platform to optimize for.
`timezone`	No	Optional IANA timezone for the returned recommendation.
`mediaType`	No	Optional content media type hint for best-time recommendations.
`platforms`	No	Optional platform set to optimize across.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedMay 7, 2026

removedInput schema / anyOf

Removed value: -[
-  {
-    "required": [
-      "platform"
-    ]
-  },
-  {
-    "required": [
-      "platforms"
-    ]
-  }
-]

First observedMay 5, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already indicate read-only and idempotent behavior, and the description aligns by stating 'without creating a post,' reinforcing a non-mutating operation. The description adds clarity about the two modes but does not disclose potential edge cases (e.g., no available slots) or return format. Given the annotations carry the safety profile, this is adequate though not exhaustive.

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

Conciseness5/5

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

The description is a single, well-structured sentence that front-loads the main action, scopes it with two modes, and adds a key non-side-effect qualifier. Every word earns its place with no redundancy or filler.

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?

Given the tool has 7 parameters with 100% schema coverage and read-only annotations, the description is mostly sufficient. It clearly identifies the purpose and modes, but it does not describe the output structure or behavior in edge cases (e.g., no suggestion available). For a simple suggestion tool, this is a minor gap, so a 4 is justified.

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?

All parameters have descriptive schema entries covering 100% of coverage, so the description does not need to add much. It does mention the mode distinction ('best-time insights or configured queue slots'), which aligns with the mode enum, but it does not add details beyond the schema's existing descriptions. Baseline of 3 is appropriate.

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?

The description uses a specific verb ('suggest') with a clear resource ('next recommended publish time') and explicitly states it does not create a post, distinguishing it from scheduling tools. It also mentions the two operating modes (best_time and queue), clarifying its scope and purpose.

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?

The description provides context on when to use this tool ('next recommended publish time' with 'best-time insights or configured queue slots') and explicitly notes it operates 'without creating a post', implying it is for recommendations, not scheduling. However, it does not explicitly name sibling alternatives or exclusions (e.g., suggest_queue_slots or schedule_content), so it falls short of full guidance.

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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TDQS

B3/5.0

Disambiguation2/5

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.

Naming Consistency3/5

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.

Tool Count1/5

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.).

Completeness3/5

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.

Resources

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