Get the processing status of a reference-image search job. Example: 'Is my reference-image search finished yet?'
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Job ID returned by submit_reference_image_search. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool gets 'processing status' but does not disclose possible status values, whether it's read-only, or any other behavioral traits. While adequate for a simple poll, it lacks extra context that would help an agent.
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 concise sentences: a clear statement and an example question. No unnecessary text, front-loaded with the core purpose.
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 simple one-parameter polling tool without an output schema, the description is fairly complete. It explains the purpose and parameter. However, it could mention possible status outcomes for better completeness.
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 has 100% coverage with a description for job_id. The description adds an example question but no additional semantics beyond what the schema provides. Baseline 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 'Get the processing status of a reference-image search job' and provides an example question, making the purpose specific and distinct from sibling tools like submit_reference_image_search.
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 description implies usage for polling job status via the example, but does not explicitly state when to use this tool vs alternatives or when not to use it. No exclusions or alternatives mentioned.
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 serves a distinct purpose: searching creatives, advertiser profiles, game rankings, image similarity search workflow, etc. Overlaps like find_similar_creatives vs submit_reference_image_search are clearly separated by whether using an existing creative or a new image URL.
All tool names follow a consistent verb_noun pattern (e.g., get_creative_detail, search_advertisers, submit_reference_image_search) with snake_case. No mixed conventions or vague verbs.
12 tools cover the domain of mobile game ad intelligence without redundancy. The count feels appropriate—enough to handle common tasks (search, detail, rankings, image search) without overwhelming.
The tool set covers essential workflows: finding creatives via text or image, analyzing advertiser and game rankings, retrieving creative details and insights, and generating briefs. The async image search workflow is fully supported with submit, status, and results tools.
