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 states the tool configures an API token, implying a write or setup operation, but does not disclose key behavioral traits such as whether this persists across sessions, requires specific permissions, has side effects (e.g., overwriting existing config), or error handling. This leaves significant gaps for a configuration tool with no annotation 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 a single, efficient sentence: 'Configure your Gemini API token for nano-banana image generation.' It is front-loaded with the core action and context, with zero wasted words. Every part of the sentence contributes to understanding the tool's purpose, making it highly concise and well-structured.

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 complexity as a configuration operation with no annotations and no output schema, the description is incomplete. It does not cover what happens after configuration (e.g., success response, error cases), how it interacts with sibling tools like 'generate_image', or behavioral details. For a tool that likely mutates state or sets up critical API access, more context is needed to be fully helpful.

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% description coverage, with the 'apiKey' parameter well-documented as 'Your Gemini API key from Google AI Studio.' The description adds no additional parameter semantics beyond this, as it does not explain format, validation, or usage context for the key. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the heavy lifting without extra value from the description.

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: 'Configure your Gemini API token for nano-banana image generation.' It specifies the verb ('configure') and resource ('Gemini API token'), and mentions the context ('nano-banana image generation'). However, it does not explicitly differentiate from sibling tools like 'get_configuration_status' or 'get_last_image_info', which might be related to configuration or image info, so it misses full sibling distinction.

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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing a token before generating images), exclusions (e.g., not for editing images), or direct alternatives among the sibling tools. The context 'for nano-banana image generation' implies a use case but lacks explicit when/when-not instructions.

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 burden of behavioral disclosure. It effectively describes key behaviors: it operates on the last image in the session (stateful behavior), supports iterative editing, and can use reference images. However, it doesn't mention potential limitations like session persistence, error handling, or output format, leaving some gaps for a mutation 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 front-loaded with the core purpose in the first sentence, followed by usage guidance and behavioral details in subsequent sentences. Every sentence adds value: the first defines the tool, the second specifies use cases, and the third explains the automatic image selection. There is no wasted text 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?

Given no annotations and no output schema, the description does well by explaining the tool's purpose, usage, and key behavior (automatic use of last image). However, as a mutation tool with 2 parameters, it could benefit from more detail on output (e.g., what is returned) or error conditions, though the schema covers parameters adequately.

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 fully documents both parameters (prompt and referenceImages). The description adds no additional parameter semantics beyond what's in the schema, such as examples or constraints not captured in the schema descriptions. This meets the baseline for high schema coverage.

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 specific action ('continue editing'), the resource ('the LAST image that was generated or edited in this session'), and distinguishes it from siblings by specifying it automatically uses the previous image without a file path, unlike edit_image which likely requires explicit image input. The verb+resource combination is precise and unambiguous.

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 this tool ('for iterative improvements, modifications, or changes to the most recent image') and provides a clear alternative context by mentioning it automatically uses the previous image, implying edit_image should be used for other images. It also distinguishes from generate_image by focusing on editing rather than creation.

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 burden of behavioral disclosure. It mentions the tool edits existing files and uses reference images, but lacks details on permissions, side effects, error handling, or output format. For a mutation tool with zero annotation coverage, this is a moderate gap, though the core action is clear.

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 that are front-loaded with the main purpose and usage guideline. Every word earns its place, with no redundancy or fluff, making it highly efficient and easy to parse.

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 complexity (editing images with mutations), lack of annotations, and no output schema, the description is adequate but incomplete. It covers the basic purpose and usage but misses behavioral details like what the tool returns or potential side effects, leaving gaps for an AI agent to operate safely.

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 parameters thoroughly. The description adds minimal value beyond the schema, only implying that 'imagePath' must be exact and 'referenceImages' are optional for tasks like style transfer. Baseline 3 is appropriate as the schema does the heavy lifting.

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 ('Edit') and resource ('a SPECIFIC existing image file'), distinguishing it from sibling tools like 'generate_image' (creates new) and 'continue_editing' (continues previous edits). The specificity about modifying existing files is explicit and well-articulated.

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 provides clear context for when to use this tool ('when you have the exact file path of an image to modify'), which implicitly distinguishes it from 'generate_image' (for new images) and 'continue_editing' (for ongoing edits). However, it doesn't explicitly mention when NOT to use it or name alternatives, keeping it at a 4.

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 full burden. It states this creates a 'NEW image' which implies a write/mutation operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, output format, or error conditions. The description adds basic context about creating from scratch but lacks richer behavioral details.

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 with zero waste. The first sentence states the core purpose, the second provides crucial usage guidance. Every word earns its place, and 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 single-parameter tool with 100% schema coverage but no annotations and no output schema, the description provides adequate purpose and usage guidance. However, it lacks information about what the tool returns (no output schema) and doesn't address potential behavioral aspects like generation time, quality constraints, or failure modes that would be helpful for a generative 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 description coverage is 100%, so the schema already fully documents the single 'prompt' parameter. The description adds minimal value by reinforcing that the prompt should describe a 'NEW image to create from scratch', but this is essentially repeating what's in the schema description. Baseline 3 is appropriate when schema does the heavy lifting.

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 'Generate' and resource 'image', specifying it's 'from text prompt' and 'NEW'. It explicitly distinguishes from sibling tools by stating 'not when modifying an existing one', which contrasts with 'edit_image' in the sibling 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 provides explicit usage guidance: 'Use this ONLY when creating a completely new image, not when modifying an existing one.' This clearly defines when to use this tool versus the 'edit_image' sibling alternative, with a strong exclusion statement.

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 full burden. It states the tool checks configuration status, which implies a read-only operation, but doesn't disclose behavioral traits like what 'configured' means (e.g., valid token, permissions), error handling, or response format. The description is minimal and lacks context beyond the basic purpose.

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, efficient sentence with zero waste. It's front-loaded with the core purpose, making it easy to parse quickly without unnecessary elaboration.

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 simplicity (0 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what the check entails (e.g., returns boolean, error details), how it integrates with other tools, or provide context for use. For a configuration-check tool, more behavioral detail would be helpful despite the low complexity.

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 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter details (as there are none), but this is appropriate given the empty schema, warranting a baseline score above minimum.

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 with a specific verb ('Check') and resource ('Gemini API token configuration'), making it immediately understandable. It doesn't distinguish from siblings like 'configure_gemini_token' (which would be the complementary write operation), but it's unambiguous about what it does.

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?

No guidance is provided on when to use this tool versus alternatives. While it's implied this should be used to verify token configuration status, there's no explicit mention of prerequisites (e.g., use before calling other tools), exclusions, or how it relates to sibling tools like 'configure_gemini_token'.

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 full burden. It discloses key behavioral traits: it retrieves information about the 'last generated/edited image in this session,' implying session-scoped data and that it's read-only (consistent with 'get' verb). However, it doesn't specify what happens if no image exists or error 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?

The description is perfectly concise with two sentences that each earn their place: first states the core purpose, second provides crucial usage guidance. No wasted words, front-loaded with essential 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 tool with no annotations and no output schema, the description provides good context about what information is retrieved and when to use it. However, it doesn't describe the return format or what specific fields (beyond 'file path, size, etc.') are included, which would be helpful given no output schema.

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 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters, maintaining focus on tool purpose. A baseline of 4 is appropriate for zero-parameter tools where 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 specific verb ('Get information') and resource ('last generated/edited image'), specifying what information is retrieved (file path, size, etc.). It explicitly distinguishes this tool from its sibling 'continue_editing' by indicating this tool provides information needed for that operation.

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 provides explicit guidance on when to use this tool: 'to check what image is currently available for continue_editing.' It clearly connects usage to a specific sibling tool and context (checking availability before continuing editing).

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