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

With no annotations provided, the description carries the full burden. It discloses the side effect of saving to disk, the return format (absolute paths), how to view results (pass to read_image), and the cost implication. This is substantial coverage, though it omits potential timeouts or network behavior that could be relevant given the timeout parameter.

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?

Three sentences with zero fluff. The main action is front-loaded, the trigger conditions follow, and the return/cost note is placed at the end. Every sentence earns its place.

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 is complete for a generate-and-save tool. It explains the return value (paths), how to view results, and the cost constraint. The schema already covers all parameter details, so nothing essential is missing for an agent to call it 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?

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning beyond what the schema already documents; it only rephrases the purpose. It does not compensate for any schema gaps, as there are none, but it also adds no extra insight.

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 states a specific verb and resource: 'Generate an image from a text prompt and save it to disk.' It also lists trigger verbs (draw, create, render, illustrate, etc.) that clearly distinguish it from the video-generating sibling, making the purpose unmistakable.

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 explicitly states when to call ('when the user asks to draw, create, render...') and even adds a cost-based usage rule ('call it once per explicit user request'). However, it does not name alternatives or exclusions (e.g., don't use for video), so it lacks the explicit when-not guidance that would merit a 5.

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 provided, the description carries the full behavioral burden. It discloses that the call is asynchronous and waits one to three minutes, that it saves to disk, and that it returns the absolute file path, task id, and wait duration. This is strong transparency, though it could also mention details like overwrite behavior or failure conditions.

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?

Three sentences with no fluff: purpose, async behavior, invocation condition, and return values are each covered. The most decision-relevant information is front-loaded, and every sentence earns its place.

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 tool with six parameters, no annotations, and no output schema, this description is complete enough for an agent to select and call it correctly. It explains the operation, the asynchronous waiting behavior, the supported input scope, and the return values, while the schema fully documents each parameter.

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?

Input schema coverage is 100%, so the baseline is 3. The description adds little parameter-specific meaning beyond the schema; it only reinforces that prompts are text-only via the unsupported-reference note. The schema descriptions themselves are already detailed, so no compensation 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 uses a specific verb and resource: 'Generate a short video from a text prompt and save it to disk.' It also clearly distinguishes itself from sibling tools by stating that reference images and videos are not supported, which separates it from generate_image and any editing/referencing workflows.

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 gives explicit when-to-use guidance: 'Call it only when the user explicitly asks for a video.' It also specifies exclusions ('reference images and videos are not supported'), but it does not explicitly name alternative tools such as generate_image for image-generation cases, so it falls just short of full routing 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?

No annotations are present, so the description carries the full burden. It is read-only in nature ('Report'), and it discloses a meaningful behavioral detail: the API key's presence is reported but its value is never exposed. This is more than a minimal description, though it stops short of explicitly stating that it has no side effects.

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 dense but every clause adds information: what is reported, what is deliberately hidden, and when to call it. No filler or repetition exists.

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?

With no parameters and no output schema, the description fully covers what an agent needs: it lists the returned configuration contents and the circumstances under which to invoke the tool. Nothing essential is missing.

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, so the baseline is 4. The description doesn't need to add parameter meaning; instead, it appropriately explains what the tool returns, which is the relevant information for an agent.

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 uses a specific verb ('Report') and a clear resource ('the current configuration'), then enumerates exactly what is included. The enumerated contents (provider, models, defaults, output directory, API key presence, model constraints) clearly distinguish this from the sibling generate_image, generate_video, and set_config tools.

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 gives explicit when-to-use guidance: 'Call this before changing settings, or when the user asks which model is in use.' This tells the agent exactly when this tool is appropriate relative to set_config and the generation tools.

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 disclosure burden, and it does substantial work: it discloses persistence ('persist them to the config file'), partial-update semantics ('Only the fields passed are changed and everything else is preserved'), and effect timing ('Changes take effect on the next call with no restart'). It does not cover behavior on invalid values or error responses, which keeps it at a 4.

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?

Three sentences, each earning its place: the first states the core action, the second gives when-to-use triggers, the third clarifies semantics and effect timing. Information is front-loaded and there is zero filler or redundancy.

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 9-parameter, all-optional config tool with no annotations and no output schema, the description covers purpose, invocation triggers, persistence, partial-update behavior, and effect timing, while the schema fully documents every parameter. The main gap is the absence of any statement about return values or failure/validation behavior, but nothing critical for correct invocation is missing.

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 description coverage is 100%, so every parameter already carries a meaningful description in the schema itself, setting the baseline at 3. The description adds a small but useful cross-parameter semantic — 'Only the fields passed are changed' — clarifying that omitted parameters are preserved, but it does not need to and does not duplicate param-level detail.

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 states a specific verb and resource ('Change settings and persist them to the config file') and elaborates with concrete use cases: 'switch a model, change a default size, output directory or timeout, or change provider.' This clearly differentiates it from siblings generate_image and generate_video (generation tools) and get_config (read-only access), so an agent can distinguish them without opening schemas.

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 gives explicit trigger conditions ('Call this when the user asks to switch a model, change a default size, output directory or timeout, or change provider'), which is clear, actionable guidance. It does not explicitly name get_config as the alternative for reading config or state when not to call the tool, so it stops short of the full 5, but the context is unambiguous.

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