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 clearly signals a destructive action and identifies the exact object being removed ('temporary upscaled file from GCS'), which helps prevent misuse. It does not disclose idempotency, auth requirements, or behavior on invalid/missing URLs, but the simple cleanup context softens that gap.

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?

One tightly written sentence carrying action, object, timing, and endpoint with zero filler. The most important information is front-loaded.

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 one-parameter cleanup operation, the description provides the essential workflow context: delete the temporary GCS file after downloading it. It leaves error behavior and idempotency unspecified, but an agent has enough to invoke it correctly in the intended pipeline.

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% and already provides strong meaning: the single parameter is a signed GCS URL from upscale_image response. The description adds only the endpoint query-string form, so it does not need to compensate further.

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?

States a specific action (delete) and resource (temporary upscaled file in GCS), reinforced by the HTTP DELETE method and path. It clearly distinguishes itself from sibling generation/upscale tools as the cleanup counterpart.

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?

Explicitly conditions use on 'after downloading', giving clear timing context. It does not name alternatives or exclusions, but no competing delete tool exists among siblingsebb, and the reference to upscale_image makes the workflow relationship implicit.

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 usefully discloses the generation modes, supported models, cost per image, and the POST endpoint. It does not, however, describe the expected response format, whether generation is asynchronous, or any authentication/rate-limit behavior, which are material for an agent invoking the 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 compact and information-dense: purpose, modes, models, cost, and endpoint are packed into three short sentences with no filler. The core purpose is front-loaded.

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 generation tool with no output schema and no annotations, the description covers invocation basics (modes, models, pricing, endpoint) and the schema covers parameters. The main gap is the absence of any statement about what the tool returns or whether results come back synchronously, which an agent would need after calling it.

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 schema already documents all five parameters. The description repeats model names that are already enumerated and gives no new meaning for parameters like count, aspectRatio, or referenceImages, so it adds little beyond 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 opens with the specific verb 'Generate' and the resource 'images', and distinguishes the two supported modes (text-to-image and image-to-image). It also lists the available models, so an agent can immediately know what this tool does and can tell it apart from video generation or upscaling 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 establishes clear context: it is for generating images rather than video/upscaling. However, it never explicitly says when to prefer this tool over a sibling or when not to use it, so the guidance is only implied by the resource name and sibling tool names.

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 bears full responsibility for disclosing behavior. It does reveal that credits are only charged on success, which is useful, but it omits critical behaviors: it does not state that the call is asynchronous (job submission) nor that the user should subsequently poll simplengat_video_status. It also does not mention any side effects beyond credit deduction, prerequisites like pre-uploaded images (though schema covers some), or response format.

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 two concise sentences, front-loaded with the core action and modes. The second sentence adds pricing and the endpoint, which are directly useful. It is not overly verbose and every part earns its place, though it could be more structured by separating pricing from endpoint, but it remains efficient.

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 10 parameters, no output schema, and no annotations, the description is insufficiently complete. It fails to explain the overall workflow: that this tool submits an asynchronous job that must be polled via simplengat_video_status. It also does not mention authentication requirements, rate limits, or any error-handling expectations. The description provides only the basic action and pricing, leaving the agent without crucial context for correct invocation and follow-up.

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% (all parameters have descriptions), so the baseline is 3. The description adds value by explaining the credit cost per resolution, which is not in the schema, and by presenting the modes in shorthand. However, it does not add significant meaning to individual parameters beyond what the schema already provides, such as the required relationship between startImage and i2v modes.

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 action ('Submit video job'), the resource (video), and enumerates the four modes (T2V/I2V/R2V/I2V-FL) that define the tool's scope. It also includes the endpoint, distinguishing it from sibling tools like simplengat_generate_image and simplengat_video_status by the explicit 'video job' phrasing and mode list.

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 generating videos but does not explicitly contrast with alternatives such as simplengat_generate_image or simplengat_video_status. It mentions pricing and success-based charging, which hints at when it might be used (e.g., to submit a job), but there is no guidance on when not to use it or what conditions make it the right choice over other 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 burden of behavioral disclosure. It does mention costs (image ~0.25 credits, video ~3 credits), which is useful, but it fails to disclose whether the tool is read-only or actually invokes generation endpoints (which would consume credits). It also doesn't mention potential side effects (e.g., creating test artifacts), rate limits, or authentication requirements. For a health check that may incur costs, this is a significant transparency gap.

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 sentence that packs purpose, cost details, and usage guidance efficiently. It is front-loaded with the core action ('Health check SimpleNGAT') and includes the overall result format. No wasted words, though it is slightly dense with Indonesian/English mixing, but that is not a structural flaw.

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 tool has no output schema, so the description must clarify the return value. It states 'Overall: healthy/degraded/down,' giving a high-level status, but it does not describe whether detailed per-service status is included or how polling works (though pollVideo is in schema). For a health check tool, the description is minimally adequate but could be more complete by indicating the response structure and any error cases.

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 schema already documents all five parameters with defaults and meanings. The description adds minimal value beyond repeating cost hints (e.g., 'image ~0.25 kredit' mirrors the checkImage description). It does not explain parameter interactions or edge cases. With full schema coverage, the baseline is 3, and the description does not meaningfully augment it.

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's purpose: 'Health check SimpleNGAT' with a specific verb and resource. It distinguishes itself from siblings (generate image, video, etc.) by focusing on health status and explicitly mentioning it returns 'healthy/degraded/down.' The scope (api+voices, image, video) is specified, leaving no ambiguity about what it checks.

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 use: 'Gunakan saat dicurigai outage/maintenance' (use when suspected outage/maintenance). This is clear usage guidance. However, it does not explicitly mention when not to use or point to alternative tools, though the sibling list makes it obvious that generation tasks should use other tools. The guidance is sufficient for an agent to select it correctly.

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 behavioral burden; 'List' and 'GET /api/v1/voices' clearly signal a read-only, side-effect-free operation. It does not mention response format or error behavior, but for a zero-parameter list operation the core behavioral trait is adequately transparent.

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 with the key action, resource, and endpoint, with no filler. Every word carries information.

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 zero-parameter list endpoint, the description is nearly complete: it states the purpose and HTTP method. The only slight gap is the unexpanded 'R2V' acronym and lack of any note about response shape, though the meaning is largely inferable.

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%, so there are no parameter semantics to explain. The 0-parameter baseline of 4 is appropriate; the description would not benefit from parameter 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 uses a specific verb ('List') and resource ('supported voices') and scopes them to 'R2V video generation'. It also provides the endpoint, making the operation unmistakable and clearly distinct from the sibling generation/upscale/status 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?

The phrase 'for R2V video generation' implies the tool is used when the agent needs available voice options for that workflow. However, it does not explicitly state when to prefer it over alternatives or any exclusions, so the guidance is only implied.

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 mentions the API endpoint and pricing but does not disclose side effects (e.g., whether the original is modified or a new image is created), authentication needs, or rate limits. Significant behavioral gaps.

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?

Single sentence front-loads the action and target, then adds pricing and endpoint. Efficient with no filler, though the endpoint could be omitted as it's likely in the schema.

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 upscale tool with 2 parameters and no output schema, it covers the core action and inputs but omits return format, whether the operation is synchronous, and how to retrieve the upscaled image. Adequate but not thorough.

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 both parameters are already documented. The description repeats 'Default 2k' but adds no new semantics beyond the schema, meeting 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?

States a clear verb ('Upscale') and resource ('generated images') with resolution options (2K/4K). Distinguishes from generate/delete siblings by action, though it doesn't explicitly name alternatives.

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?

Provides cost conditions ('Free for 2K; 4K VIP only') and references the input from generate_image, but doesn't explicitly state when to use this tool vs. alternatives or when not to use it. Usage is implied but not explicit.

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 must carry the behavioral burden. It communicates a read-only GET operation and hints at the returned information, but it does not disclose authentication requirements, possible errors, or response shape.

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 two short fragments with no filler. The action and resource are front-loaded, and the endpoint is included without 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 zero-parameter, read-only endpoint, the description is largely sufficient to invoke the tool correctly. Gaps like auth behavior and exact return fields exist, but the simplicity of the tool reduces their impact.

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?

There are zero parameters, so the baseline is 4 per the rubric. The description adds value by naming example response fields ('credits, role'), even though 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 uses a specific verb ('View') and a specific resource ('SimpleNGAT user info'), then reinforces it with the exact endpoint GET /api/v1/user/me. This clearly distinguishes the tool from the sibling image/video/voice 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?

The intended use is clear: retrieve the current user's credits, role, and related account info. There is no overlap with siblings, so no explicit exclusion is needed, though the description does not spell out 'use this when you need current user account details' in those words.

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 an important side effect: polling 1080p automatically triggers upscale when 720p finishes. However, it does not mention return format, error behavior, rate limits, or whether the operation is safe/read-only. The disclosed upscale behavior adds value but many gaps remain.

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 sentences with no fluff; the purpose is front-loaded. The endpoint at the end is mildly redundant but not distracting. It earns a 4 for efficiency without being overly sparse.

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 adequate for a simple polling tool: it gives the core action and the key 1080p upscale behavior. However, with no output schema and no annotations, it omits details like return values, polling cadence, and error conditions. There are noticeable gaps for an agent to fully understand behavior, so it is not complete.

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 baseline is 3. The description adds context around the 'resolution' parameter by explaining that 1080p triggers upscale, but it does not add meaning beyond what the schema already describes for jobId or upscaleJobId. It reaches baseline but does not elevate it.

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: 'Poll video generation status.' It clearly distinguishes this from siblings like simplengat_generate_video or simplengat_upscale_image by indicating it is a status-checking operation. The endpoint reference reinforces the purpose.

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 after video generation by saying 'poll' and explains the 1080p upscale trigger, but it does not explicitly state when to use this tool versus alternatives or give conditions like when not to use it. Usage context is present but not fully explicit.

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