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aidelly

by io.github.wilzer

aidelly_list_queues

Read-onlyIdempotent

GET /queues — list workspace content queues with slot schedules and channel assignments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNoOptional query overrides for endpoints with sparse parameter schemas.
cursorNo
offsetNo
brand_idNo
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.

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / cursor
      Added value: +{
+  "maxLength": 512,
+  "type": "string"
+}
  2. 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."
  3. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful detail about the returned content (slot schedules and channel assignments) but does not disclose pagination behavior or response format, which would be valuable.

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?

A single, front-loaded sentence includes the HTTP method, resource, and key data points. Every word earns its place, and the structure allows quick scanning.

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

Completeness3/5

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

For a simple read-only list with strong annotations, the description is adequate at a high level. However, with no output schema and six parameters (including pagination and an opaque query object), the description leaves gaps around how to use parameters and what the response will contain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33%, with only workspace_id documented. The description names the resource but explains none of the parameters (limit, cursor, offset, brand_id, query), so it fails to compensate for the large undocumented portion of the schema. The agent must guess at parameter semantics.

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 'list' and the resource 'workspace content queues', adding the HTTP method 'GET /queues' and specific content ('slot schedules and channel assignments'). This distinguishes it from other list tools and conveys exactly what the tool does.

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 context is clear: this is a read-only list operation for queues. No explicit exclusions or alternatives are mentioned, but the straightforward purpose makes the intended usage obvious. The lack of sibling differentiation is acceptable for a generic list tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All aidelly toolsInspect
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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