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

No annotations are present, so the description must disclose behavioral traits. It only states 'create an arc,' without mentioning side effects, mutation aspects, or how it integrates with existing geometry. The description is minimal.

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 very short (one sentence), making it concise, but it lacks structure. Important details like default angles and segments are not front-loaded. A bit more structure would improve clarity.

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?

With 9 parameters and no output schema, the description is incomplete. It doesn't explain how the arc is created (e.g., in the active model), what happens to existing entities, or the return value. Important context is missing.

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 78%, so most parameters are already described in the schema. The description adds little beyond what the schema provides, only repeating 'center, radius, start/end angles.' It does not clarify default behaviors or units beyond degrees.

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 it creates an arc in SketchUp and mentions key parameters (center, radius, angles). This distinguishes it from sibling tools like create_circle (full circle) or create_polygon (polygon).

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 given on when to use this tool vs alternatives, or when not to use it. It does not mention prerequisites or context, such as whether an active model or entity is needed.

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 responsibility for behavioral disclosure. It only states that the tool creates a box, without disclosing side effects, permissions, error conditions, or whether it modifies existing geometry.

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 sentence that is efficiently front-loaded with the action and key parameters, containing no unnecessary words.

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?

With 6 parameters, no output schema, and no annotations, the description is somewhat incomplete. It does not explain post-creation state, the meaning of layer and material, or any return value, leaving gaps for a complete understanding.

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 meaning for width, depth, height (dimensions) and origin (base corner), but does not describe the layer and material parameters, which are in the schema. Schema coverage is 67%, and the description does not fully compensate.

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 creates a 3-D box (rectangular prism) by specifying width, depth, height, and optionally an origin. This is a specific verb and resource that distinguishes it from sibling tools like create_circle or create_polygon.

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 the tool should be used when a box shape is needed, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusion cases.

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 mentions return type ('edges') but omits critical traits: whether the circle is added to the model, how missing layer/material parameters are handled, error conditions (e.g., non-positive radius), or whether the operation is reversible.

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 efficient—two sentences with no extraneous words. It front-loads the action and key inputs, achieving maximum clarity in minimal space.

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 and the 67% schema coverage, the description should compensate for missing annotations, output schema, and parameter semantics. It fails to address layer/material usage, default behaviors, or error handling, leaving significant gaps for a production 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?

The description merely echoes parameter names (center, normal, radius) already documented in the schema, adding no new constraints or context. It ignores segments, layer, and material, which lack schema descriptions (33% uncovered). The description does not enhance understanding beyond the schema.

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 ('Create'), the resource ('circle'), and the key inputs ('center point, normal vector, and radius'), aligning with the tool name. It also specifies the output ('Returns edges'), making the tool's purpose unambiguous and distinct from siblings like create_arc or create_polygon.

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 such as create_polygon or create_arc. It lacks any context about preferred scenarios, prerequisites, or exclusions, leaving the agent blind to selection 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. It states the creation and placement behavior and return values. However, it does not disclose potential side effects like unique name requirements, undo behavior, or permission needs, which would be helpful for a creation 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 one sentence plus a return statement, front-loaded with the key action. No unnecessary words; every part 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 moderate complexity of creating a component and placing an instance, the description covers the basic flow and return values. However, it lacks details about where the component definition is stored, whether the instance is placed at the origin or relative to the origin parameter, and any constraints on the name (e.g., uniqueness).

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 67% (name and origin have descriptions, description parameter has none). The tool description adds no additional meaning beyond what the schema already provides. It does not clarify the missing schema description for the 'description' parameter or elaborate on the format of 'origin'.

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 specifies the action (create) and resource (new empty component definition) with a side effect of placing one instance. It explicitly states the return values, distinguishing it from sibling tools like 'place_component' that place existing components.

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 does not provide guidance on when to use this tool vs alternatives. For example, it does not mention that to place an existing component, one should use 'place_component' instead. Usage context is implied but not explicit.

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 exist, so the description must bear full burden. It only restates the function without revealing behavioral traits such as whether the edge is added to the current model, if it checks for duplicates, or if it requires a specific drawing context. The description adds little beyond the tool name.

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, front-loaded sentence that conveys the essential purpose without wasted words. Every word earns its place, making it highly efficient for a simple tool.

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 simple creation tool with no output schema and moderate schema coverage, the description is minimally adequate. It covers the core intent but omits details about default behavior (e.g., layer default), return value, and side effects. Given the complexity, more context would improve 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?

The schema already describes start and end with '[x, y, z]' format, and the description offers no additional meaning. The 'layer' parameter lacks a description in both schema and description. With 67% schema coverage, the description fails to compensate for the missing layer info or to provide any semantic enrichment.

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 'Create' and resource 'edge' (line segment), and specifies it operates between two 3D points. This distinguishes it from sibling tools like create_arc, create_box, etc., which create different shapes.

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 (e.g., create_face, create_polygon). There is no mentioning of prerequisites, context, or limitations, leaving the agent without explicit 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. It lacks disclosure of what happens if points are non-planar, whether the face is added to the current model, or any side effects. Only mentions unit assumption.

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 short sentences with no redundant information. Every part is essential, and the key action 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?

Given the tool's simplicity and complete schema coverage, the description is adequate but lacks usage guidelines and behavioral details. It would benefit from mentioning when to use this vs. create_polygon.

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 has 100% description coverage, so baseline is 3. The description adds value by clarifying that points are in inches (or metric), which is not in the schema.

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 it creates a flat face from an ordered list of 3D points, specifying units. It does not explicitly differentiate from sibling tools like create_polygon, but the purpose is specific and actionable.

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 (e.g., create_polygon, create_edge). It does not mention prerequisites or exclusions.

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 provided; description only states creation of empty group but does not disclose side effects, interaction with selection, or potential overwriting 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?

Single, direct sentence with no wasted words—optimal conciseness.

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?

Description is adequate for a simple two-parameter creation tool but lacks details like default behavior when name is omitted or interaction with layers.

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 coverage is 100% with basic descriptions; tool description adds no extra meaning beyond what the schema already provides, earning baseline 3.

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 uses specific verb 'Create' and resource 'empty named group in SketchUp', clearly distinguishing from sibling tools that create arcs, boxes, circles, etc.

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 on when to use this tool vs alternatives like create_component, no prerequisites or when-not-to-use conditions.

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, the description must disclose behavioral traits. It only says 'Create a regular polygon' but doesn't explain side effects, what kind of entity is created (e.g., face, group), or requirements like planarity. The agent cannot infer if the operation is additive, destructive, or requires specific permissions.

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 sentence of 14 words, front-loading the essence. Every word is informative, and there is no redundancy or filler.

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 7 parameters, no output schema, and no annotations, the description is insufficient. It doesn't explain what the tool returns or how the polygon is integrated (e.g., as a SketchUp entity). The agent lacks critical context to use the tool correctly.

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 coverage is 71%, so the schema already describes most parameters. The description adds no extra meaning beyond what 'regular polygon' implies. For the undocumented parameters 'layer' and 'material', the description provides no help. Baseline 3 is appropriate as the schema carries the burden.

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 creates a regular polygon with n sides, using the verb 'create' and specifying the resource (regular polygon) with examples (triangle, pentagon, etc.). It effectively distinguishes from siblings like create_circle or create_box which create different shapes.

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 such as create_circle or create_face. There is no mention of prerequisites, context, or when not to use it, leaving the agent without decision support.

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 mentions 'accurate geometry', 'proper web patterns', 'angled members', and 'realistic connections', but does not disclose whether the tool creates components, groups, or modifies existing geometry. The lack of output schema and side-effect details limits 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 concise: four sentences covering purpose, types, features, and a resource link. Every sentence adds value with no redundancy. The purpose is front-loaded, and the structure is clear.

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 (9 parameters, no output schema), the description covers purpose, parameter semantics, and provides a resource for detailed guidance. However, it does not explain the output (e.g., grouping, orientation) or how the origin parameter relates to truss placement, leaving some gaps.

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 coverage is 100%, so baseline is 3. The description adds value beyond the schema by specifying span ranges for each truss type (e.g., king up to 26', fink 20-60'), which is absent from the parameter descriptions. This helps an agent choose type based on span.

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 'Create engineered roof trusses' with specific verb and resource. It distinguishes from generic sibling tools (create_box, create_circle, etc.) by detailing truss types (king post, fink/W-truss) and spans, making it unmistakably for roof trusses.

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 context with span ranges for each truss type (king up to 26', fink 20-60') and recommends a resource for further guidance. While it doesn't explicitly say when not to use, the specificity implies usage for roof truss creation, which is clear given sibling tools are generic shapes.

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?

The description discloses that code can modify or delete model data, a key behavioral trait. Without annotations, it carries the full burden and does so well, though it could mention error handling or restrictions.

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 sentences, front-loaded with purpose and context, no redundant information. Every sentence serves a clear role.

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?

The description provides return information and destructive warnings, but lacks details on error handling, sandboxing, or limitations. Given no output schema, some additional context would be helpful but is not critical.

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 covers the parameter description, but the description adds significant context about the execution context (SU_MCP module, API access) beyond the schema, providing meaningful value.

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 executes arbitrary Ruby code in SketchUp, with specific context (SU_MCP module) and API access. It distinguishes from sibling tools which are all modeling operations, not code execution.

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?

While the description warns to use with care, it does not explicitly state when to use this tool vs alternatives. However, no alternative tools exist for code execution, so the lack of explicit guidance is partially mitigated.

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, the description carries the full burden. It only states the basic operation without disclosing behavioral traits such as destructiveness, required selections, or effects on other entities.

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 extremely concise: one sentence plus a clarifying note. No unnecessary words or repetition.

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 output schema and no annotations, the description is too sparse. It does not explain extrusion behavior, constraints, or what happens to the original face, leaving the agent with an incomplete understanding.

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 coverage is 100% and descriptions are present but minimal. The tool description adds no new meaning beyond the schema (e.g., 'array of edge IDs' is already in the schema). Baseline 3 applies.

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 ('Extrude a face along a path') and the resource, which is distinct from sibling tools like create_face or push_pull. However, it does not explicitly differentiate from siblings, though the context makes it clear.

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 on when to use this tool versus alternatives like push_pull or create_face. The description only explains what the tool does, not when it is appropriate.

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. It discloses that the tool is a read operation returning general information with no side effects. It does not mention potential error conditions (e.g., no model open) but the behavior is straightforward.

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, well-structured sentence that front-loads the action and resource, then lists the specific outputs. Every word is necessary, and there is no extraneous 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?

The tool is simple with no parameters and no output schema. The description adequately covers what the tool returns. However, it could be slightly improved by mentioning the return format (e.g., object vs string) or error handling, but for a basic info tool, it is sufficient.

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, and the schema coverage is 100%. The description adds value by enumerating the returned information types, compensating for the lack of an output schema. Baseline for 0 parameters is 4.

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 uses a specific verb ('Get') and resource ('general information about the currently open SketchUp model'), and lists the exact types of information (name, file path, unit system, counts). This clearly distinguishes it from sibling tools like list_entities or create_edge.

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 when to use the tool (when needing model-level metadata) and contrasts with sibling list tools by specifying the information scope. However, it does not explicitly state when not to use it or name alternatives.

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, the description carries full burden but only says 'list all component definitions'. It does not disclose traits like read-only nature, scope (model-level?), or whether it returns nested definitions.

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?

A single, clear sentence with no unnecessary words.

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 simple list tool with no parameters and no output schema, the description is minimally adequate but lacks details about what exactly a component definition entails or how results are structured.

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 no parameters, so the baseline is 4. The description does not need to add parameter info, and schema coverage is 100%.

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 uses a specific verb ('List') and resource ('component definitions') and clearly distinguishes from siblings like list_entities or list_layers.

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 states the tool lists all component definitions, implying use when you need component definitions. No explicit exclusions or alternative suggestions, but the context is clear and siblings are differentiated by resource type.

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 only states it lists entities but does not disclose return format, whether the list is flat or hierarchical, or performance implications. For a listing tool, more behavioral details are needed.

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 entity types and scope. Every word is necessary; no wasted 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?

The tool has no output schema, so the description should explain the return format (e.g., list of entity IDs or names). It does not, leaving the agent unsure about what the response contains. For a simple one-parameter tool, more completeness is expected.

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 already provides a full description for the only parameter (group_name), covering both when it is provided and omitted. The main description adds no additional meaning beyond the schema, so baseline 3 applies.

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 'list', specifies the resource types (faces, edges, groups, component instances), and indicates the scope (model or named group). It effectively distinguishes from sibling tools like list_components.

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 explains when to use the tool (model vs. inside a group) but does not explicitly mention when not to use it or suggest alternatives like list_components for filtering by type. The context is clear but lacks exclusion 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?

With no annotations provided, the description should disclose behavioral traits. It only states the action and output (list layers with visibility) but does not clarify whether the operation is read-only, has side effects, or requires any permissions. For a simple list operation, the lack of explicit transparency is a 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 a single, concise sentence that directly conveys the tool's function. It is front-loaded and contains no unnecessary words, though it could be slightly expanded for completeness.

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 has no parameters and no output schema, the description provides essential information: it lists all layers with their visibility. This is fairly complete for a simple list operation, though it might benefit from mentioning if default layers are included or how visibility is represented.

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?

There are zero parameters in the input schema, so the baseline is 4. The description adds meaning by specifying what is listed (all layers/tags) and what information is included (visibility), which complements the empty schema.

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: 'List all layers (tags) in the SketchUp model with their visibility.' This is a specific verb ('list') and resource ('layers/tags'), and it is distinct from sibling tools which are mostly creation and transformation 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. There is no mention of use cases, exclusions, or prerequisites for listing layers.

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?

Without annotations, the description carries the burden. It informs that the tool retrieves all materials with their colors and textures, which is a clear read-only behavior. No side effects or permissions are mentioned, but for a list operation this is fairly transparent.

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 sentence that conveys exactly what the tool does without any filler. It is 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?

For a simple listing tool with no parameters and no output schema, the description is mostly complete. It tells what is returned (materials with colors and textures). However, it could mention ordering or format, but not critical.

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 zero parameters, so the description does not need to add parameter semantics. The baseline score of 4 is appropriate as the description adds no redundancy.

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 'List all materials in the SketchUp model with their colors and textures.' It uses a specific verb ('list') and resource ('materials'), and distinguishes from sibling tools like list_components or list_layers.

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. There is no mention of context, prerequisites, or exclusions, which is a gap given the variety of list tools available.

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. It only states the translation action without explaining any behavioral details (e.g., whether it's relative or absolute, collision handling, or side effects). This is insufficient for safe agent usage.

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, front-loaded sentence that contains no superfluous words. Every part contributes to the core purpose.

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 simple move command, the description covers the main function, but it omits details like coordinate system, units, or whether the movement is cumulative. Given no output schema, some return value context would be 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?

Schema coverage is 100%, so the baseline is 3. The description adds minimal extra meaning beyond the schema's parameter descriptions; it mainly restates the vector concept.

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 (move/translate), the resource (entity), and the method (by vector [x, y, z]). It effectively differentiates from sibling tools like rotate_entity and scale_entity.

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, such as push_pull or translate operations. It lacks explicit context or 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 full burden. It only states the action but fails to disclose important behaviors such as what happens if the component name is not found, whether the operation is reversible, or any side effects on the model.

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?

A single sentence of 15 words that efficiently communicates the main purpose. No unnecessary words, and the key 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?

Given the lack of output schema, annotations, and limited parameter descriptions, the description is insufficient. It does not address return values, error conditions, prerequisites (component must exist), or default behavior (e.g., orientation, scaling).

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 covers 50% of parameters with descriptions (name has a description, origin does not). The description adds 'given origin' but does not clarify the coordinate system or expected format beyond the schema's minItems/maxItems. Partial compensation for missing schema 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 uses a specific verb ('place') and identifies the resource ('instance of an existing component definition') and context ('into the model at a given origin'). It clearly distinguishes from sibling tools like create_component (which creates definitions) and list_components (which lists them).

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 the tool is for placing an instance of an existing component, but it does not explicitly state when to use it versus alternatives (e.g., when to create a component first). No when-not or exclusion criteria are provided.

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 must fully disclose behavioral traits. It explains the effect of distance on direction but omits side effects (e.g., destructive nature, constraints like planar faces, or reversibility). This is insufficient for a geometry-modifying operation.

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, front-loaded with the core purpose, and no superfluous information. Every sentence earns 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 simple tool with two required parameters and no output schema, the description adequately covers the core functionality. However, it lacks context on prerequisites (e.g., entity must be a planar face) or potential side effects, which 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%; both parameters have descriptions. The tool description adds minimal additional meaning beyond the schema (essentially restating the distance parameter's behavior). Baseline 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 verb (push/pull), resource (face), and distinguishes the tool by specifying that positive distance extrudes and negative pulls. This differentiates it from sibling tools like move_entity or scale_entity.

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 for extruding or pulling faces but does not explicitly state when to use this tool versus alternatives like move_entity or follow_me. No exclusions or contrasting guidance is provided.

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 present, the description should fully disclose behavioral traits. It only states the action without mentioning side effects (e.g., in-place modification), error handling, or authorization needs.

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 consists of a single, clear sentence that conveys the core operation without any fluff. Every word 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?

Despite having no output schema and no annotations, the description does not explain return values, side effects, or required permissions. For a 4-parameter tool with no structured metadata, this is insufficient.

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 for all 4 parameters. The description does not add additional meaning beyond what the schema already provides, so a baseline 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 identifies the verb 'rotate' and the resource 'entity', specifying rotation around an axis by an angle in degrees. This distinguishes it from sibling tools like move_entity or scale_entity.

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 such as move_entity or scale_entity. The description lacks any contextual advice about prerequisites or exclusions.

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, the description must cover behavioral traits. It describes input formats but does not disclose side effects (e.g., if scaling is destructive, permissions required, or return value). The tool likely mutates the entity, but this is not stated.

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 sentences, front-loaded with the core action, then details. No unnecessary words.

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?

The description covers parameter usage adequately but lacks information about return values, side effects, or constraints (e.g., positive scale values). Given the low complexity (3 params, no nested objects), it is partially complete but misses 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 coverage is 100%, providing a baseline of 3. The description adds value by explaining the scale parameter can be a number or array for uniform/non-uniform scaling, which is partially in the schema but clarified here. The origin parameter is also described.

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 scales an entity, specifying two modes: uniform scaling with a single number and non-uniform scaling with an [x, y, z] array. This differentiates it from sibling tools like move_entity or rotate_entity.

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 explains how to use the tool (uniform vs non-uniform, optional origin) but does not explicitly state when to choose this tool over alternatives or any exclusions. Usage is implied through the parameter explanations.

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