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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read-only query but doesn't disclose response format, pagination, error conditions, or performance characteristics. For a tool with 4 parameters and no output schema, this leaves significant gaps.

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 earns its place, making it appropriately concise for the tool's complexity.

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 4 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'available' means operationally, how results are returned, or error handling. For a query tool with multiple filtering parameters, 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?

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional parameter semantics beyond implying filtering by requirements, which is already covered by the parameter descriptions in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as checking drone availability for deliveries with specific requirements, using a specific verb ('check') and resource ('drones'). It distinguishes from siblings like 'list_available_drones' by emphasizing requirement-based filtering, but could be more explicit about the 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 like 'list_available_drones' or 'plan_delivery'. It mentions 'specific requirements' but doesn't clarify prerequisites, exclusions, or comparative contexts with sibling tools.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves a delivery path in GeoJSON format but doesn't disclose key behavioral traits: whether this is a read-only operation (implied by 'Get' but not confirmed), if it requires authentication, rate limits, error conditions, or what happens with invalid inputs. The mention of geojson.io adds minor context for visualization, but overall, the description lacks sufficient detail for a mutation-free tool with no 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 appropriately sized and front-loaded: it starts with the core purpose ('Get the delivery path in GeoJSON format for map visualization') and adds a useful tip ('Can be used with geojson.io') in a second sentence. Every sentence earns its place by providing value without redundancy, making it efficient and easy to parse for an AI agent.

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 (5 parameters, no output schema, no annotations), the description is partially complete. It covers the purpose and output format but lacks details on behavioral aspects (e.g., safety, errors) and doesn't explain the return values beyond 'GeoJSON format.' Without an output schema, the description should ideally hint at the response structure, but it doesn't, leaving gaps in understanding how to interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters (deliveryLng, deliveryLat, capacity, heating, cooling) with clear descriptions. The description adds no additional parameter semantics beyond what the schema provides, such as explaining how these inputs affect the GeoJSON output or their interrelationships. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract from the schema's documentation.

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: 'Get the delivery path in GeoJSON format for map visualization.' It specifies the verb ('Get'), resource ('delivery path'), and output format ('GeoJSON format'), distinguishing it from siblings like 'check_drone_availability' or 'plan_delivery' that focus on availability or planning rather than path retrieval. However, it doesn't explicitly differentiate from 'get_drone_details' or 'list_available_drones' in terms of path vs. drone data, leaving some ambiguity.

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 with 'for map visualization' and 'Can be used with geojson.io,' suggesting it's for visualizing delivery paths on maps. However, it lacks explicit guidance on when to use this tool versus alternatives like 'plan_delivery' (which might also involve paths) or prerequisites such as needing delivery coordinates. No when-not-to-use or clear alternatives are mentioned, leaving usage somewhat inferred rather than explicitly defined.

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 for behavioral disclosure. It states this is a read operation ('Get'), but doesn't mention authentication requirements, rate limits, error conditions, or what 'detailed information' includes. This leaves significant gaps for a tool with no 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 with the essential 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?

For a simple read operation with one parameter and no output schema, the description is minimally adequate. However, without annotations or output schema, it should ideally provide more context about what information is returned or any behavioral constraints, leaving room for improvement.

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%, so the schema already documents the single parameter 'droneId' adequately. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score 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 verb ('Get') and resource ('detailed information about a specific drone'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_available_drones' or 'check_drone_availability', which prevents 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. With siblings like 'list_available_drones' and 'check_drone_availability' available, there's no indication whether this tool is for retrieving metadata, status, or other details, or when it should be preferred over other tools.

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 describes the output ('list of all available drones with their capabilities') but does not specify whether this is a read-only operation, if it requires authentication, its rate limits, or pagination behavior. For a tool with no annotations, this leaves significant behavioral gaps, though it at least clarifies the return content.

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 and lists the returned capabilities in parentheses. There is no wasted verbiage or redundancy, 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 low complexity (one optional parameter, no output schema, no annotations), the description is minimally adequate. It explains what the tool returns but lacks details on behavioral traits like safety or performance. Without annotations or an output schema, the description should ideally provide more context on the operation's nature, but it meets the basic requirement for a simple listing 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 input schema has one parameter ('hasCooling') with 100% schema description coverage, fully documenting its purpose and type. The description does not add any parameter-specific information beyond what the schema provides, such as default behavior or interactions with other parameters. With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate but also does not detract.

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: 'Get a list of all available drones with their capabilities (capacity, heating, cooling, cost, max moves)'. It specifies the verb ('Get a list') and resource ('available drones'), and lists the returned capability fields. However, it does not explicitly differentiate from sibling tools like 'check_drone_availability' or 'get_drone_details', which might have overlapping or related functions.

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 does not mention sibling tools like 'check_drone_availability' (which might check availability for specific drones) or 'get_drone_details' (which might retrieve details for a single drone), leaving the agent to infer usage context. There are no explicit when/when-not statements or prerequisites.

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 outputs like cost estimate and drone assignment, but doesn't cover critical aspects such as whether this is a read-only simulation or commits to actual delivery planning, potential rate limits, authentication requirements, or error conditions. For a planning tool with 6 parameters and no annotations, this leaves significant behavioral gaps.

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 and key outputs. Every element earns its place by specifying what the tool does and what it returns. It could be slightly more structured by separating purpose from outputs, but it's appropriately sized with zero waste.

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 (6 parameters, no output schema, no annotations), the description is incomplete. It doesn't address behavioral traits, usage context, or output details beyond a high-level summary. For a planning tool that likely involves calculations and resource assignment, more context on constraints, assumptions, or result format would be 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%, providing clear documentation for all 6 parameters. The description adds no parameter-specific information beyond what's in the schema. It mentions general outputs but doesn't explain how parameters like 'heating' or 'cooling' affect the plan. Baseline 3 is appropriate since 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 tool's purpose with specific verbs ('plan a delivery route') and outputs ('cost estimate, number of moves, drone assignment, complete path planning'). It distinguishes from siblings like 'check_drone_availability' or 'get_delivery_geojson' by emphasizing comprehensive planning rather than checking or retrieving specific data. However, it doesn't explicitly contrast with 'plan_multiple_deliveries' beyond the singular vs. plural implication.

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 when to choose this over 'plan_multiple_deliveries' for single deliveries, or prerequisites like needing drone availability checks first. Usage is implied by the name and purpose but not explicitly stated.

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 'optimization' but doesn't describe what that entails (e.g., minimizing distance, time, cost), whether it's a read-only planning operation or executes deliveries, what permissions are needed, or any rate limits. For a complex multi-drone routing tool with zero annotation coverage, this is inadequate.

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. Every word earns its place—'plan routes', 'multiple deliveries', 'simultaneously', 'multi-drone optimization'—with zero waste or redundancy. It's appropriately sized for the tool's complexity.

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 (multi-drone optimization), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., routes, assignments, cost estimates), behavioral traits, or usage constraints. For a planning tool with significant operational implications, 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?

Schema description coverage is 100%, so the schema already documents the single 'deliveries' parameter and its nested structure. The description adds no additional parameter semantics beyond what's in the schema (e.g., explaining what 'capacity', 'heating', or 'cooling' mean in context). Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('plan routes') and resource ('multiple deliveries'), and specifies the optimization approach ('multi-drone optimization'). However, it doesn't explicitly differentiate from its sibling 'plan_delivery' tool, which appears to be a single-delivery version. The purpose is specific but lacks 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 like 'plan_delivery' or other drone-related tools. It mentions 'multi-drive optimization' but doesn't specify prerequisites, constraints, or when this approach is preferred over single-drone planning. No explicit when/when-not statements are present.

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