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SendIt

by io.github.Shree-git

Set Autopilot Goal

autopilot_set_goal

Set a social media goal for the AI autopilot to work toward.

The autopilot will use AI agents to plan content, generate posts, and schedule them. Example goals: 'Grow LinkedIn followers by 20%', 'Post 5x/week on Instagram about AI'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalTextYesThe social media goal to achieve
platformsYesTarget platforms (e.g. ['twitter', 'linkedin', 'instagram'])
durationWeeksNoHow many weeks to run the autopilot (1-52, default 4)
targetMetricsNoTarget metrics (e.g. { followers: 1000, engagement_rate: 0.05 })

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations indicate this is not read-only (readOnlyHint=false) and not destructive (destructiveHint=false). The description adds valuable behavioral context by explaining the side effects: the autopilot will use AI agents to plan and schedule content, which goes beyond the annotation safety profile. It also gives concrete examples of acceptable goals.

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 concise and well-structured: a clear first sentence states the purpose, a second explains behavior, and a third provides examples. No redundant or filler content.

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 4 parameters (two required), nested objects, and no output schema, the description covers the core purpose and workflow. It does not mention whether approval or planning are separate steps, but the sibling tools (autopilot_generate_plan, autopilot_approve_plan) imply a larger workflow. The description is sufficient for an agent to decide when to use this tool.

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?

The input schema covers 100% of parameters with descriptions, so the schema largely carries the burden. The description adds example goals and names platforms in the example, which slightly enriches the goalText and platforms semantics, but it does not provide additional detail for durationWeeks or targetMetrics beyond the schema.

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 clearly states the tool's function: 'Set a social media goal for the AI autopilot to work toward.' It uses a specific verb and resource, and distinguishes it from related tools like autopilot_list_goals or create_goal by focusing on the autopilot context.

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 clear context by explaining how the autopilot will work toward the goal ('use AI agents to plan content, generate posts, and schedule them'). It gives example goals that illustrate appropriate use, but does not explicitly mention when not to use it or compare with alternative tools like autopilot_generate_plan.

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