Navisworks MCP

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 generates a report but doesn't describe what that entails—e.g., whether it's a read-only operation, if it requires specific permissions, potential performance impacts (like being resource-intensive), or the output format beyond the schema's enum. 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the key action ('Generate a coordination report') and specifies the content clearly, making it easy to parse. Every part of the sentence adds value.

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 generating a report with multiple data types (clash summary, element counts, model stats), no annotations, and no output schema, the description is insufficient. It doesn't explain what the report output looks like, how to interpret it, or any behavioral aspects like error handling. For a tool with rich potential output and no structured support, more detail 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?

Schema description coverage is 100%, so the schema already documents both parameters ('format' and 'model_id') with descriptions. The description adds no additional meaning beyond implying that 'model_id' relates to a model for coordination reporting, but it doesn't clarify parameter interactions (e.g., how format affects output) or usage details. 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 ('Generate a coordination report') and specifies the content ('clash summary, element counts, and model stats'), which distinguishes it from siblings like 'nwd_get_clashes' (which likely returns raw clash data) and 'nwd_list_objects' (which likely lists objects without report generation). However, it doesn't explicitly mention the resource (e.g., a BIM model) or differentiate from 'nwd_upload' in terms of output format, keeping it from 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. It doesn't mention prerequisites (e.g., needing a valid model_id), exclusions (e.g., not for real-time data), or comparisons to siblings like 'nwd_get_clashes' for detailed clash analysis versus summary reports. This leaves the agent without context for 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the detection method ('bounding box overlap + D1 VDC rules'), it lacks critical details such as what the output looks like (e.g., clash list, severity levels), whether it's a read-only operation, performance considerations (e.g., processing time for large models), or error handling. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core purpose without unnecessary words. Every element ('Detect clashes', 'object groups', 'translated NWD model', 'bounding box overlap + D1 VDC rules') earns its place by contributing essential context, 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 complexity of clash detection (involving multiple parameters and no output schema), the description is incomplete. It lacks details on output format, error conditions, or performance implications, which are crucial for an agent to use the tool effectively. With no annotations and no output schema, the description should provide more behavioral context to compensate, but it does not.

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 (e.g., model_id as 'Base64-encoded URN', clash_type enum values). The description adds no additional meaning beyond what the schema provides, such as explaining how category filters interact or what 'hard' vs. 'soft' clashes entail. 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 specific action ('Detect clashes') on a specific resource ('object groups in a translated NWD model') using specific methods ('bounding box overlap + D1 VDC rules'). It distinguishes itself from siblings like nwd_export_report or nwd_list_objects by focusing on clash detection rather than reporting, viewpoint retrieval, or object listing.

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 translated model), exclusions (e.g., when not to use it), or comparisons with sibling tools. The agent must infer usage solely from the purpose statement without explicit contextual 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 a read operation ('Retrieve'), implying it's likely non-destructive, but doesn't specify permissions, rate limits, or response format. For a tool with zero annotation coverage, this is a significant gap in transparency about 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 a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded and every part earns its place, making it highly concise and well-structured for quick understanding.

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 (retrieving metadata with no output schema) and lack of annotations, the description is incomplete. It doesn't cover what the return values look like (e.g., format of viewpoints), potential errors, or behavioral constraints. For a tool with no structured output information, this leaves significant gaps for an agent 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?

The input schema has 100% description coverage, with the single parameter 'model_id' documented as a 'Base64-encoded URN'. The description doesn't add any extra meaning about parameters beyond what the schema provides, such as explaining what a 'saved viewpoint' entails. 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 ('Retrieve') and the resources ('saved viewpoints and camera positions from the model metadata'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'nwd_list_objects' or 'nwd_get_clashes', which might also retrieve model-related data, so it doesn't reach the highest 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. It doesn't mention prerequisites, context, or exclusions, such as whether it's for specific model types or when other tools like 'nwd_list_objects' might be more appropriate. This leaves 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 full burden for behavioral disclosure. It states this is a list operation, implying read-only behavior, but doesn't address critical aspects like pagination, rate limits, authentication requirements, error conditions, or what properties are included in the output. The description is too minimal for a tool with potential complexity.

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 states the core purpose upfront. There's no wasted verbiage, though it could benefit from slightly more detail given the lack of annotations and output 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?

Given no annotations, no output schema, and a tool that likely returns complex object data, the description is insufficient. It doesn't explain what 'model objects' are, what properties are returned, the format of results, or any behavioral constraints. The description leaves too many open questions for effective tool 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%, so the schema already documents both parameters thoroughly. The description adds marginal value by mentioning that filtering is by 'name/category', which slightly expands on the schema's 'keyword to filter objects' description. 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 tool's purpose with a specific verb ('List') and resource ('model objects and their properties'), and mentions optional filtering. It doesn't explicitly differentiate from sibling tools, but the action is distinct from export, clash detection, viewpoint retrieval, and upload operations.

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 mentions optional filtering but doesn't specify scenarios where filtering is appropriate or how this tool relates to sibling tools like nwd_get_viewpoints for similar data retrieval.

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 uploading and translating but doesn't describe what happens during translation, whether it's a long-running process, if it requires authentication, rate limits, error conditions, or what 'coordination viewing' entails. This leaves significant gaps for a tool that likely involves file processing and transformation.

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 gets straight to the point without unnecessary words. It's appropriately sized for a tool with three parameters and no complex behavioral nuances. However, it could be slightly more structured by separating the upload and translation aspects.

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 file upload and translation operations with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after upload, what 'translation' means, what format the output is in, or any error handling. For a tool that likely involves significant processing, this leaves too many unknowns.

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 doesn't add any additional meaning about parameters beyond what's in the schema, such as file format requirements, URL accessibility constraints, or project_id usage. 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 ('upload') and resource ('NWD/NWC file to APS') with the purpose of translation for coordination viewing. It distinguishes from sibling tools which focus on export, clash detection, viewpoint retrieval, and object listing rather than file upload. However, it doesn't specify what 'APS' stands for or the exact nature of 'coordination viewing'.

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. The description doesn't mention prerequisites, constraints, or relationships with sibling tools like nwd_export_report or nwd_list_objects. It simply states what the tool does without contextual usage information.

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