screener_from_image

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose that the AI reads numbers and criteria from each slide and returns combined JSON, which is useful. However, it does not mention limitations, error cases, or any side effects, so transparency is adequate but not thorough.

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 front-loaded with the core purpose. The three sentences each add useful information: what the tool does, how to send input, and what output to expect. Minor redundancy with the schema's image fields is acceptable and does not significantly bloat the description.

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?

The description explains the main input options and the general output (combined filter JSON), but it lacks detail about the structure of that JSON and does not clarify the role of the optional hint parameter. Given no output schema exists, a bit more detail about the returned filter format would make the tool easier to use correctly.

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 schema already documents all three parameters with 100% coverage, which sets the baseline at 3. The description adds some value by explaining that image_url or image_base64 are the two ways to submit an image, but it does not elaborate on the hint parameter beyond what the schema already says.

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 action—OCR an image of a screener into a structured filter—and identifies the input sources (IG carousel screenshots, filter tables, cover reels). However, it does not explicitly differentiate this tool from its siblings like screener_parse or ig_to_screener, so an agent may not immediately know which one to choose.

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 usage context is implied through the description: use this when you have an image of a screener and want structured filter output. It explains how to provide input (URL or base64) but gives no explicit guidance on when NOT to use it or which sibling tool to prefer in alternative scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.