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aidelly

by io.github.wilzer

aidelly_list_posts

Read-onlyIdempotent

List posts with optional platform, status, and date-range filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNo
fromNo
limitNo
queryNoOptional query overrides for endpoints with sparse parameter schemas.
cursorNo
statusNo
brand_idNo
platformNoSupported platform identifier. `twitter` and `x` map to the same surface; responses always normalize to `twitter`. `google_business` posts target a single Google Business Profile location identified by `platform_specific.locationName`. `mastodon` accounts are per-instance — the connected account carries its own `instance_url`.
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

A3.5/5.0
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, covering the safety profile. The description adds the filtering scope but does not disclose pagination behavior, default limits, or result normalization. No contradiction with 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 a single, front-loaded sentence with no filler. Every word contributes to the core purpose and filtering options, earning a perfect score for conciseness.

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 read-only list tool with 9 optional parameters and no output schema, the description covers the main filtering dimensions but omits pagination, brand_id, and workspace scoping. It is minimally viable for simple usage but not complete for nuanced agent decisions.

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 coverage is only 33%, so the description should compensate, but it only restates platform, status, and date-range filters. It does not explain cursor/limit pagination, brand_id, or query overrides. The description adds minor clarity by grouping to/from as 'date-range' but leaves much to the schema.

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 uses a specific verb ('List') and resource ('posts'), and mentions the key filtering dimensions. It is clear enough to distinguish from 'get_post' as a listing operation, though it does not explicitly differentiate from sibling 'aidelly_list_scheduled_posts'.

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 general use for listing posts with optional filters, but provides no explicit guidance on when to use this tool versus list_scheduled_posts, list_drafts, or get_post. It gives no exclusions or alternative recommendations, so usage context is only implied.

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