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

With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions 'add to your context' without explaining what that entails—e.g., whether this is a read-only operation, if it modifies state, requires authentication, or has side effects. No rate limits, error conditions, or output format are disclosed, leaving key behaviors opaque.

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 with no wasted words, making it easy to parse. However, it's front-loaded with minimal detail, which could be seen as under-specified rather than optimally concise. It earns a 4 for efficiency but loses a point for potential undershooting of necessary 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 no annotations, no output schema, and a vague description, the tool definition is incomplete. The description doesn't clarify what 'add to your context' means operationally, what the tool returns, or how it interacts with siblings. For a tool with one parameter but unclear behavior, this leaves significant gaps for an agent to understand its use.

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 'url' fully documented in the schema. The description adds no additional meaning beyond the schema, such as URL format examples or constraints. Baseline 3 is appropriate since the schema handles parameter documentation adequately.

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 the action ('Add') and resource ('Figma file'), but it's vague about what 'add to your context' means operationally. It doesn't distinguish this tool from its siblings (e.g., view_node, post_comment), which all involve Figma files in some way. The purpose is understandable but lacks specificity about the actual outcome.

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 like view_node or other siblings. The description implies it's for adding files, but it doesn't specify prerequisites, timing, or exclusions. This leaves the agent without clear direction on tool selection in 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 full burden for behavioral disclosure. It states the action ('Post a comment') but doesn't mention authentication requirements, rate limits, whether this is a write operation, or what happens upon success/failure. For a mutation tool with zero 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with every word earning 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 mutation tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral aspects like permissions needed. The 100% schema coverage helps with parameters but doesn't compensate for the lack of output and behavioral context.

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%, meaning all parameters are documented in the input schema. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline of 3 where 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 action ('Post a comment') and target ('on a node in a Figma file'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'reply_to_comment' or 'read_comments', which would require explicit differentiation to earn a 5.

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 like 'reply_to_comment' or 'read_comments'. There's no mention of prerequisites, context, or exclusions, leaving the agent with minimal usage direction.

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 what the tool does but lacks critical details: it doesn't specify if this is a read-only operation, what permissions are required, whether it returns paginated results, error conditions, or the format of returned comments. For a tool with zero annotation coverage, this is insufficient.

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 with zero wasted words. It is front-loaded with the core action and resource, 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 lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like safety, permissions, or output format, which are crucial for an agent to use this tool correctly. For a tool with no structured data beyond the input schema, more context is needed.

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 single parameter 'file_key' documented as 'The key of the Figma file'. The description adds no additional meaning beyond this, such as explaining what a 'file_key' is or where to find it. Baseline 3 is appropriate when 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 action ('Get all comments') and the resource ('on a Figma file'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'post_comment' or 'reply_to_comment', but the verb 'Get' versus 'post'/'reply' provides implicit 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 prerequisites (e.g., needing a valid file_key), exclusions, or comparisons to sibling tools like 'view_node' which might also retrieve file-related data.

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 performs a write operation ('Reply to'), implying mutation, but doesn't mention permissions required, whether replies are editable/deletable, rate limits, or what the response looks like. This leaves significant gaps for a mutation tool with zero annotation coverage.

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's appropriately sized and front-loaded, making it easy to understand at a glance.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, side effects, or response format, which are critical for safe and effective use. The high schema coverage helps with parameters, but overall context is lacking.

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 schema description coverage is 100%, with all three parameters clearly documented in the input schema. The description adds no additional parameter semantics beyond what's already in the schema (e.g., it doesn't explain format details or constraints for 'comment_id' or 'message'). 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 action ('Reply to') and target ('an existing comment in a Figma file'), making the purpose immediately understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'post_comment' or 'read_comments', which would require more specific differentiation to earn a perfect score.

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 like 'post_comment' (which might create new comments) or 'read_comments' (which retrieves comments). There's no mention of prerequisites, such as needing an existing comment to reply to, or contextual factors that would influence tool selection.

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 'Get[s] a thumbnail,' implying a read-only operation, but doesn't disclose any behavioral traits such as authentication needs, rate limits, error conditions, or what the thumbnail output entails (e.g., format, size). This leaves significant gaps for a 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 that front-loads the core purpose without any wasted words. It's appropriately sized for a simple tool with two parameters, making it easy for an agent to parse quickly.

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 (2 parameters, no nested objects) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it fails to address behavioral aspects or return values, leaving the agent with incomplete context for safe and effective use.

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 clear documentation for both parameters ('file_key' and 'node_id'), including format details for 'node_id'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 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 action ('Get a thumbnail') and resource ('for a specific node in a Figma file'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'add_figma_file' or 'read_comments', which would require a 5.

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, context for thumbnail retrieval, or how it relates to sibling tools like 'add_figma_file' or 'post_comment', leaving the agent without usage direction.

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