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

No annotations are provided, so the description carries full burden. It mentions generating screenshots and a use case, but lacks critical behavioral details: it doesn't specify output format (e.g., image files, base64), file type support, error handling, performance characteristics, or whether it modifies files. For a tool with no annotation coverage, this is a significant gap in transparency.

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 and front-loaded: two sentences with zero waste. The first sentence states the core purpose, and the second adds practical context. Every word earns its place without redundancy or 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?

Given no annotations, no output schema, and a tool that performs batch operations (implying complexity), the description is incomplete. It lacks information on what the tool returns (e.g., file paths, images), error conditions, or limitations (e.g., max files). For a tool with these contextual gaps, the description should provide more completeness.

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 (filePaths array, theme with enum). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain file path requirements, theme implications, or default behaviors. Baseline 3 is appropriate when the schema does all the work.

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: 'Generate screenshots for multiple files at once' specifies the verb (generate) and resource (screenshots for files). It distinguishes from siblings by emphasizing batch processing ('multiple files at once'), but doesn't explicitly differentiate from each sibling tool by name or specific use case.

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 implied usage guidance: 'Useful for documenting multiple code files quickly' suggests a context of code documentation with efficiency needs. However, it doesn't explicitly state when to use this tool versus the sibling tools (generate_code_screenshot, screenshot_from_file, screenshot_git_diff) or provide any exclusion criteria.

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 generating a 'beautiful screenshot' but doesn't specify output format (e.g., image type, size), performance aspects (e.g., rate limits, processing time), or error handling. For a tool with no annotations, this leaves significant gaps in understanding how it behaves beyond the basic action.

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 front-loaded in a single sentence that states the core purpose efficiently. There's no wasted text, and it directly communicates the tool's function. However, it could be slightly improved by structuring to include usage hints, but as is, it's appropriately sized for its content.

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 (generating visual output) and lack of annotations and output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., image format, dimensions), potential limitations, or how errors are handled. For a tool with no structured output information, the description should provide more context 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 description adds minimal meaning beyond the input schema, which has 100% coverage with clear descriptions for all parameters. It implies parameters through 'code with syntax highlighting and themes' but doesn't detail semantics like how 'language' affects highlighting or what 'theme' visually entails. With high schema coverage, the baseline is 3, as the schema does most of the work 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: 'Generate a beautiful screenshot of code with syntax highlighting and themes.' It specifies the verb ('generate'), resource ('screenshot of code'), and key features ('syntax highlighting and themes'), making the action distinct. However, it doesn't explicitly differentiate from sibling tools like 'batch_screenshot' or 'screenshot_from_file', which likely handle multiple codes or file inputs, 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 doesn't mention sibling tools such as 'batch_screenshot' for multiple codes, 'screenshot_from_file' for code from files, or 'screenshot_git_diff' for diff outputs, leaving the agent without context for selection. Usage is implied only by the tool's name and description, with no 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'auto-detects language from file extension', which adds useful context beyond the schema. However, it doesn't describe critical behaviors like output format (e.g., image type, size), error handling (e.g., for invalid file paths), or performance aspects (e.g., file size limits), leaving significant gaps for a tool that performs file I/O and image generation.

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 front-loads the core purpose ('Screenshot code directly from a file path') and adds key features ('optional line range selection', 'auto-detects language'). It avoids redundancy and wastes no words, though it could be slightly more structured by separating usage notes.

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 (file I/O, image generation, language detection) and lack of annotations and output schema, the description is incomplete. It misses details on output (e.g., image format, where it's saved), error conditions, permissions needed for file access, and how it differs from siblings. For a tool with no structured behavioral hints, this leaves the agent under-informed.

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 by hinting at 'optional line range selection' (implied by startLine/endLine) and 'auto-detects language' (not directly parameter-related). With high schema coverage, the baseline is 3, as the description doesn't significantly enhance parameter understanding.

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: 'Screenshot code directly from a file path' with the specific action 'screenshot' and resource 'code from a file path'. It distinguishes from siblings by mentioning 'from a file path' (vs. batch operations, git diffs, or generic generation), but doesn't explicitly name alternatives or contrast with all siblings like 'batch_screenshot' or 'screenshot_git_diff'.

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 through 'optional line range selection' and 'auto-detects language from file extension', suggesting it's for capturing specific code sections from files. However, it lacks explicit guidance on when to use this tool versus siblings like 'batch_screenshot' (for multiple files) or 'screenshot_git_diff' (for diff outputs), leaving the agent to infer based on parameter names and descriptions.

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 tool generates a screenshot, implying a read-only operation that produces an image, but does not disclose details such as output format (e.g., PNG, JPEG), size, permissions needed, rate limits, or whether it modifies any state. This leaves significant gaps for an AI agent to understand the tool's behavior fully.

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 front-loaded, with two sentences that directly state the tool's purpose and scope. There is no unnecessary information, and each sentence contributes to understanding the tool's function. However, it could be slightly more structured by explicitly separating purpose from usage hints.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and scope but lacks details on output (e.g., image format, handling of errors), behavioral traits, and explicit usage guidelines. This makes it minimally viable but with clear gaps for effective tool invocation.

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, providing clear details for all parameters (filePath, staged, theme). The description adds no additional parameter semantics beyond what the schema already explains, such as not elaborating on default behaviors or interactions between parameters. Since schema coverage is high, the baseline score of 3 is appropriate, as the description does not compensate with extra insights.

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: 'Generate a screenshot of git diff output' with the specific resource being git diff output. It distinguishes from siblings like 'batch_screenshot' or 'screenshot_from_file' by specifying git diff content, though it doesn't explicitly contrast with 'generate_code_screenshot' which might handle different code-related screenshots.

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 implied usage context by mentioning 'Shows changes in your working directory or staged changes,' which suggests when to use it (for git diff visualization). However, it lacks explicit guidance on when to choose this over alternatives like 'generate_code_screenshot' or 'screenshot_from_file,' and does not mention any exclusions or prerequisites.

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