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Glama

aidelly

by io.github.wilzer

aidelly_create_queue

POST /queues — create a new content distribution queue with recurring weekly time slots.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoOptional body override for endpoints with sparse parameter schemas.
nameYesQueue name
queryNoOptional query overrides for endpoints with sparse parameter schemas.
slotsYesTime slots when queue should post
brand_idNo
channelsNoChannels to post to from this queue
timezoneNoIANA timezone ID for slot times (e.g. America/New_York)
workspace_idNoWorkspace to operate in. Do not ask the user for this UUID — call aidelly_list_workspaces and use the `id` of the matching workspace. Optional for read operations; required when creating content.
idempotency_keyYes

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / workspace_id / description
      Added value: +"Workspace to operate in. Do not ask the user for this UUID — call aidelly_list_workspaces and use the `id` of the matching workspace. Optional for read operations; required when creating content."
  2. First observed

TDQS

B3.4/5.0
Behavior2/5

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

Annotations indicate a write operation (readOnlyHint false) with potential side effects (openWorldHint true) and no idempotency. However, the description fails to disclose behavior like duplicate handling, required workspace_id (described as optional but required for creation), or error conditions. No mention of rate limits or auth.

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, front-loaded sentence with the HTTP method, resource, and key feature. No wasted words.

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?

With 9 parameters, nested objects, and no output schema, the description is too brief. It omits details on how workspace_id is required for creation, idempotency semantics, and return values. The tool's place in the queue lifecycle (create then add items) is not mentioned.

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?

Schema description coverage is 78%, so baseline is 3. The description adds minimal value beyond schema descriptions (e.g., 'recurring weekly time slots' for slots). Parameters like idempotency_key and brand_id lack explanation in either the description or 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 verb ('create') and resource ('content distribution queue') with a specific feature ('recurring weekly time slots'). It distinguishes from siblings like aidelly_add_queue_items and aidelly_list_queues by focusing on queue creation.

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

Usage Guidelines3/5

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

The description implies the tool is for creating queues but does not provide explicit guidance on when to use it versus alternatives (e.g., aidelly_add_queue_items for adding content). No prerequisites, when-not-to-use, or context about the queue lifecycle are mentioned.

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

C2.2/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in approvals and post updates. For example, aidelly_action_post_approval and aidelly_post_approvals_id_action both handle approval actions, while aidelly_get_approvals and aidelly_list_pending_approvals appear to serve similar listing functions. The proliferation of HTTP-route-style names with generic prefixes (get_approvals_id, patch_posts_id) further obscures distinctions.

Naming Consistency1/5

The tool set mixes clean verb_noun names (create_post, list_posts) with HTTP-method-plus-path names (get_approvals_id, patch_posts_id, post_analytics_insights). There is no consistent pattern, and 'post' as a verb collides with the content post noun, creating confusion. The inconsistent conventions make it hard to predict tool names.

Tool Count1/5

With 124 tools, this server vastly exceeds the typical MCP server scope and the calibration threshold (50+ is extreme). Even for a comprehensive platform API, such a large surface overwhelms agents and makes selection impractical. The count is a severe mismatch for a usable MCP tool set.

Completeness4/5

The tool surface is remarkably comprehensive, covering CRUD for posts, drafts, scheduled posts, tasks, reports, webhooks, workspaces, e-commerce stores, and many more. Advanced features like approvals, repurpose jobs, and content automations are also represented. Minor gaps exist (e.g., no explicit delete for regular posts, only cancel), but the domain is well covered overall.

Resources