List recent generations on the authenticated account, newest first. REQUIRES AN API KEY: add "Authorization: Bearer acd_live_…" to this MCP server; a key is created by a signed-in human at https://aicontentdrop.com/settings/integrations.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many to return (1-50). Defaults to 10. |
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | ||
| generations | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds value by disclosing the authenticated-account scope, the newest-first ordering, and the API key requirement including how the key is created. This goes beyond the annotations without contradicting them.
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?
Two sentences with no filler; the core purpose is front-loaded and the auth requirement is essential. The all-caps 'REQUIRES AN API KEY' is slightly noisy but still concise.
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?
For a read-only list endpoint with an output schema and one optional parameter, the description covers purpose, ordering, scope, and authentication setup. It does not define what a 'generation' is or contrast with sibling tools, but those are minor given the simple scope.
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?
The input schema provides 100% coverage of the single optional limit parameter with constraints and default. The description adds nothing about parameters, so the baseline score of 3 applies.
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?
The description clearly states a specific verb ('List'), a specific resource ('generations'), and scope ('on the authenticated account'), plus the ordering ('newest first'). This is distinct from siblings like get_generation, though it does not explicitly name the alternative.
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?
The API key prerequisite and the intent ('recent generations on the authenticated account') imply when to use the tool. However, there is no explicit guidance about when not to use it or how it compares to siblings such as get_generation or search_articles.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a clearly distinct resource or action: account balance, article retrieval/search, model listing, cost estimation, generation triggering, and generation status/list. Even the two cost-related tools (list_models and estimate_credit_cost) are distinguishable, since one lists catalog prices and the other estimates a specific batch.
All tool names follow the same lowercase snake_case verb_noun pattern: generate_, get_, list_, search_, estimate_. The verbs are consistent and predictable, making it easy to guess the tool name for a desired action.
At 8 tools, the set is well-scoped for a platform covering video generation, account management, and a supporting article/knowledge base. Each tool earns its place and the count feels neither sparse nor bloated.
The core generation lifecycle is covered: estimate cost, generate, poll status, list history, and check account balance. Article search and retrieval are also covered, but the platform appears to offer image models based on list_models while only video generation is exposed, leaving an obvious generation gap.
