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Glama

SendIt

by io.github.Shree-git

Save to Library

save_to_library

Save content to your library as a draft, template, or evergreen content for reuse.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoTags for organization
textYesThe content text/caption
typeNoContent type (default: draft)
titleYesTitle for the saved content
team_idNoTeam ID to operate in team scope. Get available teams with list_teams. If omitted, uses personal scope.
categoryNoCategory for organization
mediaUrlNoMedia URL (image or video)
targetPlatformsNoWhich platforms this content is designed for
evergreenEnabledNoEnable evergreen auto-republishing
evergreenIntervalDaysNoDays between evergreen republishes

Schema Changelog

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

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

The description simply states the saving action and adds the content-type variants, which are already captured by the schema's type enum. It does not disclose any behavioral traits beyond the annotations, such as how new items are created, whether team scope is possible, or any side effects. Given minimal annotations, this leaves the agent without additional safety or workflow context.

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 concise sentence that gets to the point immediately. It avoids redundancy and front-loads the core action and target resource, making it easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 10 parameters, no output schema, and various optional fields like team_id, mediaUrl, and targetPlatforms, this description is too sparse. It does not convey the broader use case beyond basic saving, nor does it mention team scope or media-related options, leaving the agent to rely entirely on the schema.

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?

Because schema description coverage is 100%, the schema fully documents all parameters. The description adds the conceptual grouping of content types and the reuse purpose, but no syntax or relationship details beyond the enum. This meets the baseline for schema-heavy descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the action (save), the resource (library), and the content types (draft, template, evergreen), making its core purpose unambiguous. However, it does not differentiate from the sibling tool create_library_item, which likely performs a similar creation action, so it stops short of full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is provided about when to use this tool versus alternatives such as create_library_item or save_project_content_to_library. The phrase 'for reuse' hints at intent but does not state preconditions, exclusions, or alternative options, leaving the agent without clear selection criteria.

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