aidelly_list_image_editor_outputsList the workspace's saved AI-generated and edited image outputs, freshest first.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | Optional query overrides for endpoints with sparse parameter schemas. | |
| cursor | No | ||
| brand_id | No | ||
| workspace_id | No | Workspace to operate in: the `id` of a workspace returned by aidelly_list_workspaces. Optional for read operations; required when creating content. |
Changes observed during successful MCP inspections.
Input schema / properties / workspace_id / descriptionPrevious 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."New value: +"Workspace to operate in: the `id` of a workspace returned by aidelly_list_workspaces. Optional for read operations; required when creating content."Input schema / properties / cursorAdded value: +{
+ "maxLength": 512,
+ "type": "string"
+}Input schema / properties / workspace_id / descriptionAdded 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."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so safety is covered. The description adds the ordering behavior ('freshest first') and workspace scope, which is useful, but it omits pagination behavior and what 'saved' excludes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler. The scope and ordering information is packed efficiently without repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With five parameters, low schema coverage, and no output schema, the description is too thin. It does not explain pagination via cursor, the limit default/cap, or how brand_id filters results, leaving the agent to infer essential list behavior from a sparse schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 40% (2 of 5 parameters documented). The description does not clarify limit, cursor, brand_id, or the query overrides object, and adds nothing about syntax or defaults beyond what is already in the sparse schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (List), resource (workspace's saved AI-generated and edited image outputs), and ordering (freshest first). It does not name a sibling alternative, but the resource is distinctive enough that an agent can separate it from generic list tools like list_drafts or list_posts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use, when-not-to-use, or alternative-tool guidance is given. The description implies usage through the verb 'List', but provides no conditions, prerequisites, or routing hints relative to the many sibling list tools.
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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