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aidelly_post_analytics_insights

POST /analytics/insights

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoOptional body override for endpoints with sparse parameter schemas.
queryNoOptional query overrides for endpoints with sparse parameter schemas.
brand_idNo
platformsNoPlatforms to analyze for insights.
regenerateNoIf true, force regeneration even if insights exist.
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

D1.5/5.0
Behavior2/5

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

Annotations provide some cues (readOnlyHint=false, etc.), but the description adds no additional behavioral details such as side effects, auth requirements, or result expectations. It fails to compensate for the lack of annotation depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise but at the expense of clarity. It is a single line that fails to convey essential information, making it insufficient for effective tool use.

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

Completeness1/5

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

Given the tool's complexity (7 parameters, no output schema, many siblings), the description is severely incomplete. It provides no context for return values, prerequisites, or how it differs from related tools like aidelly_get_analytics_insights.

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?

With 71% schema description coverage, the schema already documents most parameters. However, the description adds no value by explaining or clarifying parameters like brand_id or query. It merely repeats the endpoint.

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

Purpose1/5

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

The description is merely 'POST /analytics/insights', a tautology that restates the HTTP method and endpoint without explaining what the tool does. It lacks a verb-resource pair and title, providing no insight into its function.

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 guidance is given on when to use this tool versus alternatives like aidelly_get_analytics_insights or aidelly_patch_analytics_insights. The description offers no context for appropriate usage.

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.