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 but doesn't describe what this entails—whether it stores the token persistently, requires specific permissions, has side effects (e.g., overwriting existing configuration), or what happens on success/failure. For a configuration tool with zero annotation coverage, this leaves critical behavioral traits unclear.

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 that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for a simple configuration tool, with zero waste 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 the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects like persistence or error handling. Without annotations or output schema, more context on what 'configure' entails would improve completeness, but it's not entirely inadequate for this simple case.

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%, with the parameter 'apiKey' fully documented in the schema (including a URL for obtaining the key). The description adds no additional meaning beyond what the schema provides, as it doesn't elaborate on parameter usage, format, or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to heavily.

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 ('configure') and the resource ('OpenRouter API token for image generation'), making the purpose understandable. It doesn't explicitly distinguish from sibling tools like 'get_configuration_status' or 'generate_image', but the verb 'configure' implies a setup action rather than retrieval or usage, providing some implicit differentiation.

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 doesn't mention prerequisites (e.g., needing an API key first), when it should be invoked (e.g., before generating images), or how it relates to sibling tools like 'get_configuration_status' for checking configuration. Usage is implied only by the action 'configure', with no explicit context.

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 explains key behaviors: it operates on the last image in the session automatically and supports iterative editing. However, it doesn't cover important aspects like whether this is a destructive operation (overwrites the last image), authentication needs, rate limits, or what happens if no previous image exists.

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 sized at three sentences, each earning its place. It's front-loaded with the core purpose, followed by usage context, and ending with the automatic behavior. Zero wasted words 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 tool with 3 parameters, 100% schema coverage, but no annotations and no output schema, the description is adequate but has gaps. It explains the core purpose and session context well, but doesn't address behavioral aspects like whether this is a read-only or destructive operation, error conditions, or return values. The lack of annotations increases the burden on the description.

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 three parameters thoroughly. The description adds minimal value beyond the schema - it mentions 'optionally using additional reference images' which aligns with the referenceImages parameter but doesn't provide additional semantic context. 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 tool's purpose with specific verbs ('continue editing') and identifies the resource ('the LAST image that was generated or edited in this session'). It distinguishes from siblings by specifying it works on the most recent image automatically, unlike 'edit_image' which likely requires explicit file paths.

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 ('for iterative improvements, modifications, or changes to the most recent image') and mentions it automatically uses the previous image. However, it doesn't explicitly state when NOT to use it or name specific alternatives like 'edit_image' for non-last images.

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 states the tool edits an existing image but doesn't disclose critical behavioral traits: whether this is a destructive mutation (overwrites the original or creates a new file), what permissions or authentication are needed, any rate limits, error handling, or the nature of the output (e.g., returns a new file path or modifies in-place). For a mutation tool with zero annotation coverage, this is a significant 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 appropriately sized and front-loaded: two concise sentences that directly state the purpose and usage context. Every sentence earns its place by providing essential information without redundancy or fluff, making it 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 complexity of an image editing tool with no annotations and no output schema, the description is incomplete. It lacks behavioral details (e.g., mutation effects, auth needs), doesn't explain the return values or output format, and relies heavily on the schema for parameters. For a tool that performs edits, this leaves significant gaps in understanding how to use it effectively.

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 four parameters (imagePath, prompt, aspectRatio, referenceImages) with descriptions. The description adds minimal value beyond the schema: it mentions 'optionally using additional reference images' (implied by referenceImages) and 'exact file path' (implied by imagePath). No additional syntax, format details, or constraints are provided, so the 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's purpose: 'Edit a SPECIFIC existing image file, optionally using additional reference images.' It specifies the verb ('edit'), resource ('existing image file'), and scope ('specific'), distinguishing it from sibling tools like 'generate_image' (creation) and 'continue_editing' (ongoing edits). However, it doesn't explicitly differentiate from all siblings (e.g., 'get_last_image_info' is informational, but this isn't mentioned).

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: 'Use this when you have the exact file path of an image to modify.' This gives a specific prerequisite (file path availability) and implies it's for modifying existing images rather than creating new ones. It doesn't explicitly state when not to use it or name alternatives like 'generate_image', but the context is sufficient for basic 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 provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool generates images via OpenRouter with a specific model, which adds useful context about the external service and generation method. However, it lacks details on potential limitations (e.g., rate limits, costs, output format, or error handling), which are important for a tool that likely involves API calls and resource consumption.

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 core purpose and usage rule. Every word earns its place by clarifying the tool's intent and distinguishing it from siblings, with no redundant or vague phrasing. It efficiently communicates essential information 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 complexity (image generation via external API) and lack of annotations or output schema, the description is somewhat incomplete. It covers the purpose and usage well but misses behavioral details like expected output format, error conditions, or dependencies (e.g., token configuration via 'configure_openrouter_token'). For a tool with no structured safety or output info, more context would be beneficial.

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%, with clear descriptions for both parameters (e.g., 'prompt' is for 'describing the NEW image to create from scratch'). The description reinforces the 'NEW' aspect for the prompt but doesn't add significant semantic details beyond what the schema already provides, such as explaining prompt best practices or aspect ratio implications. Baseline 3 is appropriate given the 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 ('Generate a NEW image'), the resource ('image'), and the method ('from text prompt using OpenRouter (Gemini 2.5 Flash Image)'). It explicitly distinguishes this tool from modification tools like 'edit_image' among its siblings by emphasizing 'creating a completely new image, not when modifying an existing one.'

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 ('ONLY when creating a completely new image') and when not to use it ('not when modifying an existing one'), which clearly differentiates it from alternatives like 'edit_image' among the sibling tools. This direct exclusion rule offers strong usage context.

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 states the action ('Check') but doesn't describe what the check entails (e.g., returns a boolean, error message, or status details), potential side effects, or authentication requirements. This leaves gaps in understanding the tool's 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?

The description is a single, clear sentence that efficiently conveys the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for a simple tool, with no wasted 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?

Given the tool's simplicity (0 parameters, no annotations, no output schema), the description is minimal but lacks completeness. It doesn't explain what the output might be (e.g., success/failure status, configuration details), which is critical for a check operation. This leaves the agent uncertain about how to interpret results.

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, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here, and the baseline score for 0 parameters is 4, as 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 clearly states the tool's purpose with a specific verb ('Check') and resource ('OpenRouter API token configuration'), making it immediately understandable. It doesn't explicitly differentiate from sibling tools like 'configure_openrouter_token', but the distinction is implied through the action (checking vs. configuring).

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 context (verifying token setup) but doesn't provide explicit guidance on when to use this tool versus alternatives like 'configure_openrouter_token' or other siblings. It lacks details on prerequisites, error conditions, or specific scenarios where this check is necessary.

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. It clearly indicates this is a read operation ('Get information') and specifies the scope ('in this session'), but doesn't disclose potential limitations like what happens if no image exists, error conditions, or session persistence details. It adds some context about the tool's role in the workflow.

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 serve distinct purposes: the first defines what the tool does, the second explains when to use it. There's zero wasted text, and the most important information (the tool's 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 zero-parameter tool with no annotations and no output schema, the description provides good context about what information is retrieved and how it fits into the workflow with 'continue_editing'. However, it doesn't specify the exact format of returned information or what 'etc.' might include, leaving some ambiguity about the output.

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 with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on the tool's purpose and usage context.

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 ('Get information about') and resource ('last generated/edited image'), including what information is retrieved ('file path, size, etc.'). It explicitly distinguishes this tool from its sibling 'continue_editing' by explaining its role in checking what image is available 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'), directly naming the sibling tool 'continue_editing' as the alternative for which this serves as a prerequisite check. This creates clear contextual boundaries.

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