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

With no annotations, the description carries the burden. It reveals key behavioral traits: local processing (no API), free, instant. It mentions compression via quality parameter. However, it omits that resizing never upsamples (present in schema but not description) and does not discuss output naming or file overwrite behavior.

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 front-load the main purpose (format conversion and resize) and then add compression. Every phrase earns its place; no fluff.

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 6-parameter conversion tool with no output schema, the description covers the main capabilities and a key benefit (no API, free). It lacks details on output behavior (e.g., overwrite, naming) but schema covers path parameters. Overall, sufficient for typical use.

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%, so parameters are well-documented in the schema. The description merely restates that the tool can convert format, resize, and compress (quality). It adds no new semantic information beyond the 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?

The description clearly states the tool converts format (png/jpeg/webp/avif), resizes, and compresses local images. It distinguishes itself from sibling tools like edit_image (editing) and generate_image (creation) by focusing on conversion/resize/compress without API.

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 use for local, instant, free conversion/resize/compression without an API. It does not explicitly state when not to use (e.g., for editing or generation), but the context of siblings and the tool's purpose provides implicit guidance.

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

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

With no annotations, the description carries full burden. It discloses that multiple images are accepted, an optional mask is used (with OpenAI model restriction), and the result is saved to disk with paths returned. However, it does not detail write behavior (overwriting), error handling, or prerequisites beyond model-specific mask support.

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 three sentences, front-loading the primary purpose with a clear directive. No redundant phrases; every sentence adds essential information (use cases, input details, output behavior).

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 7 parameters, no annotations, and no output schema, the description adequately covers the tool's main use, input expectations, and outcome (saves to disk and returns paths). It lacks output format specifics and prerequisites but is sufficient for an image editing tool.

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%, baseline 3. The description adds value by clarifying the mask parameter is only for OpenAI models (not in schema) and reinforces the purpose of each parameter through contextual usage examples. This exceeds the baseline.

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 lists the specific actions: edit existing image, generate new based on reference, combine elements, transfer style, or create variations. It explicitly states the tool is for use with starting images, distinguishing it from sibling 'generate_image' which likely generates without references.

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 begins with 'Use always when there are starting images' and lists concrete use cases, providing clear context. However, it lacks explicit 'when not to use' statements or direct references to sibling tools like 'generate_image' for no-reference generation.

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

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

With no annotations, the description carries the full burden. It discloses that images are saved to disk and that file paths are returned. This provides clear side-effect and output behavior. It could mention resource consumption or rate limits, but the given transparency is strong.

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 somewhat long but efficiently front-loads the core purpose. The important usage guideline is highlighted with 'IMPORTANTE'. Every sentence contributes value. A slight trim could improve conciseness, but it remains well-structured and reader-friendly.

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 explains return values (file paths) and side effects (saving to disk). It covers required behavior and important constraints (aspect ratio). It lacks details on error handling, rate limits, or maximum image count (4 per schema), but overall provides sufficient context for an agent.

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% (baseline 3). The description significantly enriches parameters: for 'size' it details market aspect ratios and advanced provider-specific syntax; for 'model' it hints at Google models and suggests list_image_models; for 'quality' it clarifies which models ignore it. This adds substantial value beyond the 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?

The description clearly states the tool generates images from a text prompt, saves them to disk, and returns file paths. It distinguishes from edit_image via the condition 'Se o usuário quer partir de uma imagem existente'. This provides a specific verb-resource pair and differentiates from siblings.

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 explicitly states when to use (generate from text) and when not (edit/vary/reference, use edit_image). It also includes an important guideline to ask for aspect ratio if not provided, listing market standards. This gives clear context for selection and invocation.

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

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

No annotations are provided, so the description carries the full burden. It accurately describes the read-only nature (returns info) and the type of data returned. However, it lacks details on missing files, error handling, or disk access behavior, which is acceptable for a simple tool but not exhaustive.

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 extremely concise—two sentences that front-load the tool's output and usage context. Every word adds value; no waste.

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 the tool's low complexity (one parameter, no nested objects, no output schema), the description is largely complete. It covers purpose, return values, and usage context. A slight improvement could be to mention the return format, but this is not essential.

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%, so the schema already documents the lone parameter. The description does not add extra meaning beyond what the schema provides (absolute path). 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 returns specific metadata (dimensions, format, disk size, transparency) for a local image. It uses a specific verb and resource, distinguishing it from sibling tools which perform actions like editing, converting, or generating images.

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 explicitly recommends using this tool before editing, converting, or publishing, providing clear usage context. However, it does not state when not to use it or mention alternatives.

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

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

With no annotations, the description covers key behaviors: returns public URL, default permanence, optional expiry, no authentication needed, and privacy warning. It could additionally disclose rate limits or file size caps, but the provided information is sufficient for safe use.

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, covering purpose, behavior, and a security note in a few sentences. It is not overly verbose, though it could benefit from clearer separation between purpose and behavioral details.

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 the lack of output schema, the description adequately explains the return value (public URL). It covers both modes, supported image types (from parameter), and important caveats. It is complete for a straightforward image hosting tool, missing only potential constraints like max file size.

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 has 2 parameters with 100% description coverage. The main description adds value by explaining the 'expires' parameter in terms of actual services (catbox.moe vs. litterbox) and default behavior. The 'images' parameter is adequately described in the 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?

Description clearly states it uploads local images to free hosting and returns a direct public URL. It specifies the use case: for platforms needing the image link, not the file. This distinguishes it from sibling tools like convert_image or edit_image.

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?

Description mentions no signup or API key needed, and explains the two modes (permanent vs. temporary). It provides a security warning. However, it does not explicitly contrast with alternative tools like a generic file upload, but the context of siblings makes the use case clear.

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

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

No annotations exist, so the description carries the full burden. It clearly implies a read-only list operation, which is the primary behavioral trait needed for such a tool.

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 a single, concise sentence that immediately conveys the tool's purpose without any extraneous 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?

For a parameterless list tool with no output schema, the description is adequate. It mentions both the listing and capability aspects, though it could optionally hint at the return format.

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 tool has zero parameters and schema coverage is 100% (empty schema). Per guidelines, a baseline of 4 is appropriate since no parameter documentation is needed.

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 verb ('Lista') and the resource ('modelos de geração de imagem'), and distinguishes from sibling tools which focus on individual image operations like converting or editing.

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 before generating images to see available models, but provides no explicit when-to-use or when-not-to-use guidance, nor mentions alternatives.

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