Check an assemble_video job by its job_id. Returns the status (processing, done, or error). When done, returns the final MP4 url, the aspect, clip count, total duration, and the booked cost in EUR. When it errored, returns the reason. Only jobs on your own account are visible.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | The job_id returned by assemble_video |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare idempotentHint=true and readOnlyHint=true. The description adds useful behavioral details: return format for done (MP4 url, aspect, etc.) and error (reason), plus account visibility constraint.
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?
The description is concise and well-structured, with four sentences that are front-loaded with the primary purpose. No wasted words.
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?
Given no output schema, the description covers the key return states (processing, done, error) with specific fields. It also notes account visibility. Could mention behavior for invalid job_ids, but overall sufficient.
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 coverage is 100%, and the parameter description is already provided by the schema. The tool description does not add additional semantics beyond the schema, so a baseline score of 3 is appropriate.
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 the tool checks an assemble_video job by job_id and returns status. It specifies the resource (assemble_video job) and distinguishes from siblings like clips_status or assemble_video itself.
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?
It indicates to use with job_id from assemble_video and notes that only jobs on the user's own account are visible. While it doesn't explicitly state when not to use, the context is clear enough.
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 has a clear, distinct purpose. The status checkers (assemble_status, clips_status) are differentiated by the job type they monitor. Memory tools (index, note, recall) are distinct operations. Competitor ad tools (search, get ads, get details) and video generation pipeline (avatar, clips, assembly) are well-separated.
All tools use consistent snake_case with a verb_noun or noun_verb pattern (e.g., assemble_video, get_competitor_ads, memory_index). No mixing of conventions, making the tool names predictable and easy to understand.
With 17 tools, the server covers account management, memory, competitor research, and video generation without being overwhelming. The count is well-scoped for its functionality, neither too sparse nor too heavy.
The toolset covers the core workflows: account setup (sign_up, upgrade, whoami), memory (CRUD), competitor analysis (search, get ads, details), and video ad creation (avatar, clips, assembly). Minor gaps like lacking a delete memory tool are acceptable given the domain focus.
