SendIt

Preview Content

preview_content

Read-onlyIdempotent

Generate a visual preview of how content will appear on each platform.

USE THIS WHEN: • Before publishing to see how posts will look • To validate content against platform requirements • To check character counts, hashtag limits, and media requirements

Returns an HTML preview mockup for each platform with validation results: • Character count vs limit • Hashtag count (Instagram has 30 max) • Media requirement check • Platform-specific warnings and errors

Input Schema

TableJSON Schema

Name	Required	Description	Default
`content`	Yes
`platforms`	Yes	Platforms to generate previews for

Output Schema

TableJSON Schema

Name	Required	Description	Default
`valid`	No
`errors`	No
`isError`	No
`warnings`	No
`platforms`	No
`errorMessage`	No
`followUpSuggestions`	No

Schema Changelog

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

Changed1 schema field changedMay 11, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "errorMessage": {
+      "type": "string"
+    },
+    "errors": {
+      "items": {
+        "additionalProperties": true,
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "followUpSuggestions": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "isError": {
+      "type": "boolean"
+    },
+    "platforms": {
+      "items": {
+        "additionalProperties": true,
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "valid": {
+      "type": "boolean"
+    },
+    "warnings": {
+      "items": {
+        "additionalProperties": true,
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}

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 declare the tool read-only, idempotent, and non-destructive, so the description need not repeat that. It adds useful behavioral context: returns an HTML preview mockup with specific validation results (character count, hashtag count with Instagram max, media checks, platform-specific warnings). This goes beyond the structured annotations.

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 one-sentence summary followed by a 'USE THIS WHEN' bullet list and a return-value bullet list. Every line adds value, and key information is front-loaded.

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's moderate complexity (nested content object, platform enum list, output schema), the description covers the essential aspects: purpose, typical usage, return format, and validation checks. The presence of an output schema handles return-value details. It could explicitly state that it does not publish content, but the 'preview' name and 'before publishing' context make that clear. Overall, it is complete enough for an agent to select and use the tool correctly.

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 schema describes each parameter (content, text, mediaUrl, mediaType, mediaUrls, platforms) with basic descriptions, but schema coverage is only 50%. The description adds context about how content will be validated (e.g., character counts, hashtag limits, media requirements), which helps the agent understand what the content parameter should contain. However, it does not clarify the distinction between mediaUrl and mediaUrls or how the platforms array affects output, so parameter meaning remains partially ambiguous.

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 with a specific verb and resource: 'Generate a visual preview of how content will appear on each platform.' It distinguishes itself from siblings like validate_content by emphasizing the HTML preview mockup and validation results, making the purpose unambiguous.

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 'USE THIS WHEN' section provides explicit scenarios: before publishing, validating content against platform requirements, and checking character/hashtag/media limits. It does not mention when NOT to use it or point to alternatives, but the context is strong enough to guide an agent.

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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