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. 'Create a new contact' implies a write/mutation operation, but there's no information about permissions required, whether the operation is idempotent, what happens on duplicate data, what the response contains, or any error conditions. For a creation 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 maximally concise - a single three-word phrase that communicates the core function without any wasted words. It's appropriately sized for such a basic operation and gets straight to the point.

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 creation tool with 7 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what a 'contact' represents in this system, what happens after creation, whether there are validation rules, or how this entity relates to others in the system (like customers or users). The context signals indicate significant complexity that the description doesn't address.

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 provides no parameter information beyond what's already in the schema. However, with 100% schema description coverage, all 7 parameters are well-documented in the schema itself. The baseline score of 3 reflects that the schema does the heavy lifting, though the description adds no additional context about parameter relationships or usage patterns.

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 'Create a new contact' clearly states the verb and resource, making the basic purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'create_customer' or 'create_user' - all appear to create different entity types, but the description provides no context about what distinguishes a 'contact' from these other entities.

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 sibling tools like 'create_customer', 'create_user', and 'update_contact' available, there's no indication of when a contact should be created versus these other entities, or when to create versus update an existing contact.

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. While 'create' implies a write operation, the description doesn't mention required permissions, whether the operation is idempotent, what happens on duplicate data, or what the response contains. For a mutation tool with 20 parameters, this leaves significant behavioral questions unanswered.

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 at just three words, with zero wasted language. It's front-loaded with the essential information (create operation on customer resource) and contains no unnecessary elaboration.

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 complex mutation tool with 20 parameters, nested objects, no annotations, and no output schema, the description is severely inadequate. It doesn't explain what happens after creation, what identifiers are returned, error conditions, or how this fits into the broader customer management system alongside sibling tools.

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 all parameters are documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete, but provides no extra 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 verb ('create') and resource ('customer'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'update_customer' or explain how it differs from other creation tools like 'create_contact' or 'create_project' in the same system.

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 about when to use this tool versus alternatives. There's no mention of prerequisites, when creation is appropriate versus updating existing customers, or how this relates to sibling tools like 'get_customers' or 'delete_customer' in typical workflows.

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. 'Create a new expense' implies a write/mutation operation, but it doesn't disclose critical traits such as authentication needs, rate limits, whether the creation is idempotent, what happens on failure, or the expected response format. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence—'Create a new expense'—with zero wasted words. It's front-loaded and appropriately sized for its purpose, though it could benefit from more detail. Every word earns its place by stating the core action clearly.

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 (10 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't explain what an 'expense' entails in this system, how it relates to other resources (e.g., customers, projects), or what the tool returns upon success. For a mutation tool with rich input schema but no output or behavioral hints, more context is needed to guide effective use.

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

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

Schema description coverage is 100%, meaning all parameters are documented in the input schema with descriptions (e.g., 'date' as 'YYYY-MM-DD format', 'rate' as 'expense rate/price'). The description adds no additional parameter semantics beyond this, so it meets the baseline of 3 where the schema does the heavy lifting, but doesn't compensate with extra context like examples or usage tips.

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 'Create a new expense' clearly states the verb ('Create') and resource ('expense'), which is adequate. However, it doesn't differentiate this tool from sibling tools like 'create_mileage' or 'create_project' that also create different resource types, nor does it specify what constitutes an 'expense' in this system (e.g., a billable cost vs. mileage). This makes it vague compared to more specific alternatives.

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. For example, it doesn't mention when to choose 'create_expense' over 'create_mileage' (likely for different expense types) or 'create_project' (for project creation), nor does it indicate prerequisites like required permissions or dependencies. This lack of context leaves the agent to infer usage from tool names alone.

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. 'Create a new mileage entry' implies a write/mutation operation but provides no information about permissions required, whether the operation is idempotent, what happens on failure, or what the response contains. For a creation tool with 11 parameters and no output schema, this minimal description leaves critical behavioral aspects unspecified.

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 at just four words, front-loading the essential information with zero wasted words. It follows the pattern of other sibling tools (e.g., 'create_contact', 'create_expense') consistently. For such a straightforward creation operation, this brevity is appropriate rather than under-specified.

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 (11 parameters including nested objects, 3 required parameters, no output schema, and no annotations), the description is insufficiently complete. It doesn't explain what a 'mileage entry' represents in the system's domain, doesn't mention typical use cases, and provides no information about the creation result. The 100% schema coverage helps but doesn't compensate for the lack of contextual understanding needed for proper tool invocation.

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

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

Schema description coverage is 100%, so all parameters are documented in the schema itself. The description adds no parameter information beyond what's already in the structured schema - it doesn't explain relationships between parameters, provide examples, or clarify dependencies. The baseline score of 3 reflects adequate coverage through the schema alone, though the description contributes nothing additional.

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 ('mileage entry'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'update_mileage' or 'get_mileage' by specifying it creates a new entry rather than modifying or retrieving existing ones. However, it doesn't explicitly differentiate from other creation tools like 'create_expense' or 'create_project' beyond the resource type.

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 (like needing existing customer/project/vehicle/user IDs), doesn't explain when mileage creation is appropriate versus expense creation, and offers no context about typical workflows. With multiple sibling creation tools available, this lack of differentiation is a significant gap.

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 but offers none. 'Create a new project' implies a write/mutation operation but doesn't disclose permissions needed, whether creation is idempotent, what happens on failure, rate limits, or any side effects. This is inadequate for a complex 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 extremely concise at just three words. While this represents severe under-specification, it's not verbose or poorly structured—every word directly states the tool's action. The problem is insufficiency, not lack of 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?

For a complex creation tool with 16 parameters, nested objects, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what a successful creation returns, error conditions, or the operational context. The agent lacks essential information to use this tool 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?

Schema description coverage is 100%, so the schema fully documents all 16 parameters. The description adds no parameter information beyond what's in the schema, meeting the baseline score of 3. However, it doesn't compensate for the schema's complexity by explaining relationships between parameters (e.g., how invoicing.method affects other fields).

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 'Create a new project' is a tautology that restates the tool name without adding specificity. It doesn't distinguish this tool from sibling creation tools (e.g., create_contact, create_customer) beyond the resource type, and lacks details about what constitutes a 'project' in this context.

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's no mention of prerequisites, when not to use it, or how it relates to sibling tools like update_project or delete_project. The agent receives zero contextual usage information.

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 adds valuable context about financial implications ('can result in additional invoice and extra cost'), which is crucial for a creation tool. However, it doesn't mention permission requirements, rate limits, or what the response looks like.

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. The parenthetical note about costs is relevant and earns its place. No wasted words, though it could potentially be more 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 creation tool with no annotations and no output schema, the description is adequate but has clear gaps. It covers the purpose and a key behavioral implication (costs), but doesn't address permissions, response format, or error conditions. The 100% schema coverage helps, but more behavioral context 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%, so the schema already documents all 6 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. 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 tool's purpose: 'Create a new user' specifies the verb and resource. It distinguishes from sibling tools like create_contact or create_customer by focusing on users. However, it doesn't explicitly differentiate from update_user or get_user_by_id in terms of when to use each.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides implied usage guidance through the note about additional costs, suggesting this should be used cautiously. However, it doesn't explicitly state when to use this vs. alternatives like update_user or get_users, nor does it 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 are provided, so the description carries the full burden of behavioral disclosure. 'Delete a contact' implies a destructive, irreversible mutation, but it fails to specify critical details: whether it requires specific permissions, what happens to associated data, if deletion is permanent, or what the response looks like (e.g., success/failure confirmation). For a destructive tool with zero annotation coverage, this is a significant 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, direct sentence with zero wasted words—'Delete a contact' is front-loaded and efficiently conveys the core action. Every word earns its place, making it easy for an agent to parse quickly without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a destructive mutation tool with no annotations and no output schema, the description is incomplete. It lacks essential context: behavioral risks (e.g., irreversibility), permission requirements, error handling, or output expectations. The 100% schema coverage helps with parameters, but overall completeness is inadequate for safe and effective use.

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

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

The input schema has 100% description coverage (the 'id' parameter is documented as 'Contact ID'), so the schema does the heavy lifting. The description adds no additional meaning about parameters beyond implying deletion requires an ID. This meets the baseline of 3 for high schema coverage, but doesn't enhance understanding (e.g., format constraints or examples).

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 'Delete a contact' clearly states the action (delete) and resource (contact), making the purpose immediately understandable. It distinguishes from sibling tools like 'get_contact_by_id' or 'update_contact' by specifying the destructive operation. However, it doesn't explicitly differentiate from other delete operations (e.g., 'delete_customer'), which slightly reduces specificity.

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 contact ID), exclusions (e.g., irreversible nature), or comparisons to other tools like 'update_contact' for modifications. This leaves the agent with minimal context for decision-making.

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. 'Delete a customer' implies a destructive, irreversible mutation, but the description fails to disclose critical behavioral traits: whether deletion is permanent or soft, what permissions are required, whether related data is cascaded, what happens on success/failure, or any rate limits. This is dangerously inadequate for a destructive 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?

The description is maximally concise at three words with zero wasted language. It's front-loaded with the core action and resource. While severely under-specified, what's present earns its place efficiently without redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive mutation tool with no annotations and no output schema, the description is completely inadequate. It fails to address critical context: what 'delete' means operationally, what permissions are needed, what the response contains, error conditions, or relationships to sibling tools. The agent cannot safely or effectively use this tool based on this description alone.

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% (the 'id' parameter is fully documented in the schema as 'Customer ID'), so the baseline score is 3. The description adds no parameter information beyond what's already in the schema—it doesn't explain format constraints, validation rules, or provide examples. It meets the minimum viable threshold but adds zero 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 'Delete a customer' is a tautology that merely restates the tool name. While it identifies the verb ('Delete') and resource ('customer'), it provides no additional specificity about scope, permanence, or what constitutes a 'customer' in this context. It doesn't differentiate from sibling delete tools like delete_contact or delete_project beyond the resource name.

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 absolutely no guidance about when to use this tool versus alternatives. There's no mention of prerequisites (e.g., customer must exist), consequences, or when to choose this over other customer-related tools like update_customer or get_customer_by_id. The agent receives zero 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Delete an expense' implies a destructive mutation, but it doesn't specify whether deletion is permanent, reversible, requires specific permissions, or has side effects (e.g., affecting related records). This is a significant gap for a destructive tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single sentence 'Delete an expense', which is front-loaded and wastes no words. Every part of the sentence directly contributes to the tool's purpose, making it efficient and well-structured for its brevity.

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 (destructive mutation with no annotations and no output schema), the description is incomplete. It lacks critical information such as behavioral traits (e.g., permanence, permissions), usage context, or output expectations. This makes it inadequate for safe and effective use by an AI agent.

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 1 parameter with 100% description coverage ('Expense ID'), so the schema fully documents the parameter. The description adds no additional parameter information, but with 0 parameters needing semantic clarification beyond the schema, a baseline of 4 is appropriate as it doesn't detract from the schema's completeness.

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 'Delete an expense' states the action (delete) and resource (expense), which is clear but minimal. It distinguishes from sibling tools like 'delete_contact' or 'delete_project' by specifying the expense resource, but lacks specificity about scope or permanence. It's not tautological but remains vague about what 'delete' entails.

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. For example, it doesn't mention prerequisites (e.g., needing an expense ID from 'get_expense_by_id'), exclusions, or comparisons to other deletion tools like 'delete_contact'. The description offers no context for usage decisions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool deletes a mileage entry, implying a destructive operation, but lacks details on permissions required, whether deletion is reversible, side effects (e.g., impact on related records), or error handling. This is insufficient for a mutation tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence with zero wasted words, front-loading the key action and resource. It efficiently communicates the core purpose without unnecessary elaboration.

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 destructive tool with no annotations and no output schema, the description is incomplete. It lacks critical context such as behavioral traits (e.g., permanence, authorization), usage guidelines, and expected outcomes, leaving significant gaps for an AI agent to operate safely and 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 schema description coverage is 100%, with the parameter 'id' clearly documented as 'Mileage entry ID'. The description doesn't add any semantic details beyond what the schema provides, such as format examples or constraints. Baseline 3 is appropriate since the schema adequately covers the single parameter.

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 ('Delete') and resource ('a mileage entry'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'create_mileage' and 'update_mileage' by specifying deletion, though it doesn't explicitly mention what distinguishes it from other delete operations (e.g., 'delete_contact').

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. It doesn't mention prerequisites (e.g., needing an existing mileage entry ID), exclusions, or comparisons to related tools like 'update_mileage_status' for status changes instead of deletion.

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. 'Delete a project' implies a destructive mutation, but it doesn't disclose critical behavioral traits: whether deletion is permanent or reversible, required permissions, side effects (e.g., cascading deletion of related data), error conditions, or confirmation prompts. This is a significant gap for a destructive 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 extremely concise ('Delete a project')—a single phrase with zero wasted words. It's front-loaded with the core action, making it easy to scan. Every word earns its place by conveying the essential 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?

Given the tool's complexity (destructive operation with no annotations and no output schema), the description is incomplete. It lacks details on behavioral aspects (e.g., irreversibility, permissions), usage context, and expected outcomes. For a delete tool, this minimal description leaves critical gaps for an AI agent to operate safely and 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 1 parameter with 100% description coverage ('Project ID'), so the schema fully documents the parameter. The description doesn't add any parameter details beyond the schema, but with 0 parameters to explain and high schema coverage, the baseline is 4 as it doesn't need to compensate for gaps.

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 'Delete a project' clearly states the action (delete) and resource (project), which is adequate. However, it doesn't distinguish this tool from other delete_* siblings (e.g., delete_contact, delete_customer) beyond the resource name, and it lacks specificity about what 'delete' entails (e.g., permanent removal vs. archiving).

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. For example, it doesn't mention prerequisites (e.g., ensure the project exists via get_project_by_id first), exclusions (e.g., cannot delete if active tasks exist), or comparisons to siblings like update_project for modifications. The description only states the action without context.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It states the tool retrieves data ('Get'), implying a read operation, but doesn't specify whether it requires authentication, has rate limits, returns structured data, or handles errors like invalid IDs. For a tool with zero annotation coverage, 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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality and wastes no space on redundant details, making it easy to parse quickly while conveying 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?

Given the lack of annotations and output schema, the description is insufficient for a tool that retrieves data. It doesn't explain what data is returned, format of the response, error handling, or authentication requirements. While the schema covers inputs well, the overall context for proper tool invocation remains incomplete.

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 no parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for both 'id' and 'expand'. The baseline score of 3 reflects adequate documentation through the schema alone, though the description doesn't enhance understanding of parameter usage or provide examples.

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

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

The description clearly states the action ('Get') and resource ('a specific contact by ID'), making the purpose immediately understandable. It distinguishes from sibling tools like 'get_contacts' by specifying retrieval of a single contact rather than a list. However, it doesn't explicitly differentiate from other 'get_by_id' tools for different resources, 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. It doesn't mention when to choose 'get_contact_by_id' over 'get_contacts' for multiple contacts, or how it relates to sibling tools like 'update_contact' or 'delete_contact'. There's also no indication of prerequisites or error conditions, leaving usage context entirely implicit.

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 but only states the basic retrieval action. It doesn't disclose important behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior beyond what's in parameters, or what format the contacts are returned in. The description adds minimal value 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 extremely concise - a single sentence with no wasted words. It's front-loaded with the core purpose and doesn't contain any unnecessary elaboration or repetition. This is an example of efficient communication.

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 annotations, and no output schema, the description is insufficiently complete. It doesn't help the agent understand what data is returned, how to interpret results, or provide context about the TimeChimp contact system. The agent would need to rely heavily on the parameter schema alone.

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 all parameters are well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the comprehensive schema descriptions. This meets the baseline expectation when schema coverage is complete.

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

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

The description states the basic action ('Retrieve all contacts') and resource ('from TimeChimp'), but it's vague about scope and doesn't differentiate from sibling tools like get_contact_by_id. It doesn't specify whether 'all' means literally every contact or if there are limitations like only returning active contacts by default.

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 about when to use this tool versus alternatives like get_contact_by_id or get_customers. The description doesn't mention any prerequisites, context for usage, or exclusions that would help an agent choose appropriately among the many 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get'), but doesn't describe what happens on failure (e.g., if ID doesn't exist), whether authentication is required, rate limits, or what the return format looks like. For a tool with zero annotation coverage, 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 perfectly concise - a single sentence that states exactly what the tool does with zero wasted words. It's front-loaded with the core functionality and doesn't include any unnecessary information or redundancy.

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 read operation with no annotations and no output schema, the description is insufficiently complete. It doesn't describe the return format, error conditions, authentication requirements, or how it differs from similar tools. Given the complexity of having 2 parameters and being part of a large sibling toolset, more contextual information would be helpful for an AI agent.

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

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

Schema description coverage is 100%, so the schema already fully documents both parameters (id and expand). The description adds no additional parameter information beyond what's in the schema - it doesn't explain what 'expand' does, provide examples, or clarify ID format. Baseline 3 is appropriate when the schema does all the parameter documentation work.

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

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

The description clearly states the verb ('Get') and resource ('a specific customer by ID'), making the purpose immediately understandable. It distinguishes from sibling tools like 'get_customers' (plural) by specifying retrieval of a single customer. However, it doesn't explicitly differentiate from 'get_contact_by_id' or other entity-specific getters, which keeps 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 when to use 'get_customer_by_id' instead of 'get_customers' (for bulk retrieval) or other entity-specific getters like 'get_contact_by_id'. There's also no information about prerequisites, error conditions, or performance considerations.

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 'Retrieve' implies a read operation, the description doesn't mention pagination behavior (implied by 'top' and 'skip' parameters), rate limits, authentication requirements, or what format the results will be in. This is inadequate for a tool with 7 parameters and no output schema.

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 without any wasted 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?

Given the tool's complexity (7 parameters, no output schema, and no annotations), the description is insufficient. It doesn't explain the return format, pagination behavior, or how to interpret the various filtering options. For a list retrieval tool with multiple parameters, more context is needed for the 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?

Schema description coverage is 100%, with all 7 parameters well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline of 3 for adequate but not additive 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 action ('Retrieve') and resource ('all customers from TimeChimp'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'get_customer_by_id' or 'get_contacts', which would require more specificity for 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 sibling tools like 'get_customer_by_id' for retrieving specific customers and 'get_contacts' for retrieving contacts, the agent receives no help in choosing between these related retrieval operations.

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 it's a read operation ('Get'), but doesn't mention authentication requirements, rate limits, error handling, or what happens if the ID doesn't exist. For a tool with zero annotation coverage, 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 extremely concise at just 5 words, front-loaded with the core purpose, and contains no unnecessary information. Every word earns its place in communicating the essential function.

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 read operation with no annotations and no output schema, the description is insufficient. It doesn't explain what expense data is returned, format of response, error conditions, or authentication requirements. Given the context of sibling tools that include status history and other detailed operations, this description leaves too many 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 description coverage is 100%, so the schema already fully documents both parameters. The description doesn't add any parameter semantics beyond what's in the schema - it mentions 'by ID' which corresponds to the 'id' parameter but provides no additional context about ID format, validation, or the 'expand' parameter's purpose.

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 'expense by ID', making the purpose unambiguous. It distinguishes from sibling 'get_expenses' by specifying retrieval of a single expense rather than a list. However, it doesn't mention what specific expense data is retrieved beyond the ID.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'get_expenses' or other get_by_id tools. The description implies usage when you have a specific expense ID, but doesn't address scenarios like batch retrieval or filtering by other 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?

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It states 'Retrieve all expenses' but doesn't mention pagination behavior (implied by skip/top parameters), authentication requirements, rate limits, error conditions, or what format the expenses are returned in. For a tool with 11 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 extremely concise at just 5 words, front-loading the core purpose with zero wasted words. Every word earns its place, making it easy for an agent to quickly understand the basic function before examining the detailed 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?

For a tool with 11 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain the filtering capabilities, pagination approach, or return format. While the schema covers parameter details, the description fails to provide the contextual understanding needed to effectively use this tool, especially given the complexity implied by the many filtering options.

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 provides no parameter information, but the schema has 100% description coverage with detailed documentation for all 11 parameters including defaults, formats, and examples. Since schema_description_coverage is high (>80%), the baseline score of 3 is appropriate - the schema does the heavy lifting, and the description adds no additional parameter semantics.

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 ('Retrieve') and resource ('all expenses from TimeChimp'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'get_expense_by_id' which retrieves a specific expense, nor does it mention the filtering capabilities that distinguish it from a simple list-all operation.

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 that this is for listing expenses with optional filtering versus 'get_expense_by_id' for retrieving a single expense, nor does it provide context about when filtering parameters should be used. The agent receives no usage direction beyond the basic purpose.

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 'query,' implying a read-only operation, but doesn't confirm this or describe other traits like rate limits, authentication needs, error handling, or response format. The description adds minimal behavioral context 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, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for the tool's complexity. Every word earns its place without redundancy.

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 (7 parameters, no output schema, no annotations), the description is incomplete. It lacks details on behavioral traits, usage context, and output format (e.g., what data is returned, pagination behavior). For a query tool with multiple parameters and no structured output documentation, 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 7 parameters (e.g., 'id' for expense ID, 'top' for max records). The description adds no additional parameter semantics beyond what's in the schema, such as explaining relationships between parameters (e.g., 'skip' and 'top' for pagination). 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: 'Query status history modification records of an expense.' It specifies the action ('query'), resource ('status history modification records'), and target ('an expense'). However, it doesn't explicitly differentiate from sibling tools like 'get_expense_by_id' or 'get_expenses,' which focus on expense data rather than status history.

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 an expense ID), exclusions, or comparisons to similar tools like 'get_mileage_status_history' for mileage records. Usage is implied 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?

No annotations are provided, so the description carries full burden. It states it's a 'Get' operation, implying read-only, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what happens if the ID doesn't exist. The description is minimal and lacks context 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 with zero waste. It's front-loaded with the core action and efficiently conveys the tool's purpose without unnecessary details, making it easy to scan and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete for a tool with 2 parameters. It doesn't explain return values, error cases, or behavioral context. For a read operation in a system with many siblings, more guidance on usage and output would be beneficial to ensure correct agent invocation.

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

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

Schema description coverage is 100%, so the schema already documents both parameters ('id' and 'expand') fully. The description doesn't add any meaning beyond what the schema provides, such as explaining the purpose of 'expand' or format examples. With high schema coverage, baseline 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 'Get a specific invoice by ID' clearly states the verb ('Get') and resource ('invoice'), and specifies it's for a specific item by ID. However, it doesn't distinguish from sibling tools like 'get_invoices' (plural) beyond the ID specificity, which is somewhat implied but not explicitly contrasted.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_invoices' for listing multiple invoices or clarify if this is for retrieving a single known invoice versus searching. No exclusions or prerequisites are 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 states this is a retrieval operation but doesn't mention pagination behavior (implied by 'top' and 'skip' parameters), rate limits, authentication requirements, or what format the invoices are returned in. For a 9-parameter tool with no annotations, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states the core 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 tool with 9 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain the relationship between parameters, how filtering works, what 'all invoices' means in practice, or what the return format looks like. The agent would need to infer too much from the parameter schema alone.

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 all parameters are well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

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 ('Retrieve') and resource ('all invoices from TimeChimp'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_invoice_by_id' or explain what 'all invoices' means in context of the available filters.

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 'get_invoice_by_id' for single invoices or other filtering tools. It mentions retrieving 'all invoices' but doesn't clarify if this is the primary listing tool versus filtered searches.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Retrieve') but doesn't mention whether this requires authentication, has rate limits, returns paginated results, or what format the data comes in. For a tool with 11 parameters and no annotation coverage, this leaves significant behavioral questions unanswered.

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 exactly what the tool does with zero wasted words. It's appropriately sized for a retrieval tool and front-loads the core functionality.

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 11 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'mileage entries' contain, what format they return in, or how to interpret the various filtering options. The agent would need to rely heavily on the parameter schema alone without contextual guidance.

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

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

The schema description coverage is 100%, with all 11 parameters well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline of 3 for high schema coverage without adding 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 verb ('Retrieve') and resource ('all mileage entries from TimeChimp'), making the purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'get_mileage_by_id' or 'get_mileage_status_history', but the scope ('all') provides some implicit distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_mileage_by_id' for single entries or 'get_mileage_status_history' for status changes. There's no mention of prerequisites, access requirements, or typical use cases for retrieving all mileage entries versus filtered subsets.

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 this is a read operation ('Get'), but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or what happens if the ID doesn't exist. For a retrieval tool with zero annotation coverage, this is a significant 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, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple retrieval 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?

Given the tool's low complexity (simple retrieval), 100% schema coverage, and no output schema, the description is minimally adequate. However, with no annotations and missing behavioral details (like error cases), it doesn't fully prepare an agent for reliable invocation, keeping it at the minimum viable level.

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

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

Schema description coverage is 100%, so the schema already fully documents both parameters (id and expand). The description doesn't add any meaning beyond what the schema provides—it mentions 'by ID' which is redundant with the schema's parameter description. Baseline 3 is appropriate when the schema does all the work.

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

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

The description clearly states the verb ('Get') and resource ('a specific mileage entry by ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_mileage' (which likely lists multiple entries) or 'get_mileage_status_history' (which focuses on status changes), missing full sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_mileage' for listing entries or 'get_mileage_vehicle_by_id' for vehicle details, leaving the agent to infer usage from naming patterns alone.

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 only states the tool queries records, implying a read-only operation, but lacks details on permissions, rate limits, pagination behavior (beyond what's in the schema), error handling, or return format. For a tool with 7 parameters and no output schema, 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 with zero wasted words. It's front-loaded with the core purpose and appropriately sized for the tool's complexity. Every word earns its place, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, no annotations, no output schema), the description is incomplete. It doesn't address behavioral aspects like authentication needs, rate limits, or what the query returns (e.g., list of status changes with timestamps). Without annotations or output schema, the description should provide more context to help the agent understand the tool's full behavior and 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?

The schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how 'filter' or 'orderby' expressions work in practice). This meets the baseline of 3 for high schema coverage, but doesn't provide extra 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's purpose: 'Query status history modification records of a mileage entry.' It specifies the verb ('Query'), resource ('status history modification records'), and scope ('of a mileage entry'). However, it doesn't explicitly differentiate from sibling tools like 'get_expense_status_history' or 'get_mileage_by_id', which would be needed for 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 mileage entry ID), compare it to similar tools like 'get_expense_status_history', or specify use cases (e.g., auditing changes). This leaves the agent with insufficient context for optimal 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. It only states the basic action ('Get') without mentioning any behavioral traits such as read-only nature, authentication requirements, error handling, rate limits, or what happens if the ID doesn't exist. This leaves significant gaps for a tool that likely queries data.

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 is appropriately sized and front-loaded, making it easy to understand at a glance, with no wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, permissions, or response format, which are crucial for a retrieval tool. While the schema covers parameters well, the overall context for an AI agent to use this tool effectively is insufficient, especially compared to sibling tools that might have similar 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?

The input schema has 100% description coverage, with clear documentation for both parameters ('id' and 'expand'). The description doesn't add any meaning beyond the schema, such as explaining the format of 'id' (e.g., numeric ID) or examples for 'expand'. However, since the schema coverage is high, the baseline score of 3 is appropriate as the schema handles the parameter semantics adequately.

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

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

The description clearly states the action ('Get') and resource ('a specific mileage vehicle by ID'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'get_mileage_vehicles' (which likely lists all vehicles) or 'get_mileage_by_id' (which retrieves mileage entries rather than vehicles), missing explicit differentiation.

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. For example, it doesn't specify if this is for retrieving a single vehicle's details after listing vehicles with 'get_mileage_vehicles', or clarify its role compared to other 'get_*_by_id' tools like 'get_mileage_by_id'. The description offers no context or exclusions for usage.

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 states it's a retrieval operation, implying read-only behavior, but doesn't disclose pagination behavior (implied by 'top' and 'skip' parameters), rate limits, authentication needs, or what 'active_only' means in practice. This leaves significant behavioral gaps for an agent.

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 and wastes no space, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete for a tool with 7 parameters. It doesn't explain return values (e.g., list structure, fields), error handling, or how parameters like 'filter' and 'orderby' (OData expressions) should be used, leaving the agent with insufficient context for reliable invocation.

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

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

Schema description coverage is 100%, with all 7 parameters well-documented in the schema (e.g., 'top' for max results, 'skip' for pagination). The description adds no parameter semantics beyond the schema, so it meets the baseline of 3 where the schema does the heavy lifting.

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

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

The description clearly states the verb ('Retrieve') and resource ('all mileage vehicles'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'get_mileage_vehicle_by_id' or 'get_mileage', which might retrieve specific vehicles or mileage records rather than vehicles themselves.

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. With siblings like 'get_mileage_vehicle_by_id' (for a specific vehicle) and 'get_mileage' (for mileage records), the description lacks context on choosing between list vs. detail views or related resources.

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 states it's a read operation ('Get'), implying non-destructive behavior, but lacks details on permissions, rate limits, error responses, or output format. For a tool with 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 with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple retrieval 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?

Given no annotations, no output schema, and a read operation with two parameters, the description is incomplete. It doesn't explain what data is returned, error handling, or usage context. For a tool in a set with many siblings, more guidance would help the agent use it 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 description coverage is 100%, so the schema fully documents both parameters ('id' and 'expand'). The description adds no parameter-specific information beyond implying the 'id' is required. Baseline 3 is appropriate as the schema handles 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 verb ('Get') and resource ('a specific project by ID'), making the purpose unambiguous. It distinguishes from sibling tools like 'get_projects' (plural) by specifying retrieval of a single project, though it doesn't explicitly contrast with other 'get_by_id' tools (e.g., 'get_contact_by_id').

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. It doesn't mention prerequisites (e.g., needing a valid project ID), contrast with 'get_projects' for listing multiple projects, or specify error conditions (e.g., what happens if the ID doesn't exist).

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 states 'Get' implying a read operation, but doesn't disclose behavioral traits like authentication needs, rate limits, data freshness, or whether this aggregates real-time vs. historical data. For a financial insights 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?

Single sentence, front-loaded with the core purpose, listing key data types efficiently. No redundant words or structural issues—every part of the description 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?

Given one parameter with full schema coverage and no output schema, the description is minimally complete for a read operation. However, as a financial insights tool with no annotations, it should do more to explain return format (e.g., structured metrics vs. raw data) and usage context. It's adequate but has clear gaps in behavioral context.

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

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

Schema description coverage is 100% for the single parameter 'id', so the schema already documents it as 'Project ID'. The description doesn't add meaning beyond what the schema provides—it doesn't clarify format constraints or example values. Baseline 3 is appropriate when schema handles parameter 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 action ('Get') and the resource ('project insights'), specifying the data types included (hours, budget, costs, revenue). It distinguishes from siblings like 'get_project_by_id' by focusing on insights rather than basic project details. However, it doesn't explicitly contrast with 'get_projects' for listing multiple projects.

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 explicit guidance on when to use this tool versus alternatives like 'get_project_by_id' or 'get_projects'. The description implies usage for detailed financial/metric insights on a specific project, but lacks clear exclusions or prerequisites. It doesn't mention if this is for reporting vs. operational purposes.

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 but offers minimal behavioral information. It doesn't disclose whether this is a read-only operation, what authentication is required, rate limits, pagination behavior beyond the 'skip' parameter, or what format the returned projects will have. 'Retrieve all projects' implies a list operation but lacks crucial implementation details.

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 maximally concise with a single clear sentence that states the core functionality without any wasted words. It's appropriately sized for a straightforward retrieval operation and front-loads 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 tool with 7 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'projects' contain, how results are structured, authentication requirements, or error conditions. The agent would need to guess about the return format and operational constraints despite the tool's complexity.

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 no parameter information beyond what's already in the schema, which has 100% coverage with detailed descriptions for all 7 parameters. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, though the description could have provided context about how parameters interact or typical use cases.

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 ('Retrieve') and resource ('projects from TimeChimp'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_project_by_id' or 'get_project_insights', which would require more specificity about scope or filtering capabilities.

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's no mention of when to choose 'get_projects' over 'get_project_by_id' for single projects, or 'get_project_insights' for analytical data, leaving the agent without contextual usage instructions.

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

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

With no annotations provided, 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 behavior (e.g., what happens if the ID doesn't exist), or response format. For a tool with zero annotation coverage, 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 perfectly concise at just 5 words, front-loading the essential information with zero wasted words. Every word earns its place in conveying 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 read operation with no annotations and no output schema, the description is insufficient. It doesn't explain what a 'tag' represents in this system, what information is returned, or how this differs from the sibling 'get_tags' tool. The context signals show this is a simple tool, but more completeness 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 description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any additional meaning about the parameters beyond what's in the schema. The baseline of 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 verb ('Get') and resource ('a specific tag by ID'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'get_tags' (which presumably lists all tags), missing an opportunity for full differentiation.

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 'get_tags' or other get_by_id tools. There's no mention of prerequisites, error conditions, or typical use cases for retrieving a single tag versus listing all tags.

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 but only states the basic action without disclosing behavioral traits. It doesn't mention whether this is a read-only operation, potential rate limits, authentication needs, pagination behavior, or what the return format looks like (especially critical without an output schema).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with zero wasted words. It's appropriately sized and front-loaded with the essential purpose, making it highly efficient.

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 (7 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain return values, pagination behavior, error conditions, or how parameters interact (e.g., combining filter with active_only). For a list retrieval tool with rich filtering options, 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 7 parameters with descriptions, defaults, and constraints. The description adds no additional parameter information beyond what's in the schema, meeting the baseline for high 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 ('Retrieve') and resource ('all tags from TimeChimp'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_tag_by_id' or explain scope beyond 'all tags' (e.g., filtering capabilities mentioned in parameters).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'get_tag_by_id' for specific tags or other list tools. The description lacks context about prerequisites, typical use cases, or comparison 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?

With no annotations provided, the description carries full burden but only states the basic action. It lacks details on permissions, rate limits, error responses, or whether it's a safe read operation (implied by 'Get' but not explicit). This is inadequate for a tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core purpose, making it easy to scan and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and a read operation with two parameters, the description is incomplete. It doesn't cover behavioral aspects like safety, error handling, or return format, leaving significant gaps for an AI agent to use the tool 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?

Schema description coverage is 100%, so parameters 'id' and 'expand' are documented in the schema. The description adds no additional meaning beyond implying 'id' is required, which is already in the schema. Baseline 3 is appropriate as the schema handles parameter 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 'Get a specific task by ID' clearly states the verb ('Get') and resource ('task'), specifying retrieval by ID. It distinguishes from sibling tools like 'get_tasks' (plural) by focusing on a single task, but doesn't explicitly contrast with other 'get_*_by_id' tools (e.g., 'get_contact_by_id').

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. It doesn't mention prerequisites (e.g., needing a valid task ID), contrast with 'get_tasks' for listing, or specify error handling for invalid IDs, leaving usage context unclear.

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 only states the action ('Retrieve') without mentioning whether this is a read-only operation, if it requires authentication, potential rate limits, or what the return format looks like. This leaves significant gaps for a tool with 8 parameters and no output schema.

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 tool with 8 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the return format, pagination behavior, error conditions, or how it differs from sibling tools. The description should provide more context given the tool's complexity and lack of structured metadata.

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%, providing detailed documentation for all 8 parameters. The description doesn't add any additional parameter information beyond what's already in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.

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

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

The description clearly states the verb ('Retrieve') and resource ('all tasks from TimeChimp'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_task_by_id' or 'get_projects', which would require mentioning this tool's scope of returning all tasks rather than specific ones.

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 'get_task_by_id' or 'get_projects', nor does it mention prerequisites or context for usage. It merely states what the tool does without indicating appropriate scenarios.

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 but offers minimal information. It doesn't mention whether this is a read-only operation (implied by 'Retrieve' but not explicit), authentication requirements, rate limits, pagination behavior beyond what's in parameters, error conditions, or response format. For a tool with 10 parameters and no annotations, this is inadequate behavioral context.

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 with zero wasted words. It's appropriately sized for a retrieval tool and front-loads the essential information. Every word earns its place in this minimal but complete statement of 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 tool with 10 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what a 'time entry' contains, what the typical response looks like, authentication requirements, or error handling. The schema handles parameter documentation well, but the description should provide more context about the operation's behavior and results given the tool's complexity.

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

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

The schema description coverage is 100%, with each parameter well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in description, which applies here.

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 'Retrieve' and resource 'time entries from TimeChimp', making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_time_entry_by_id' or other 'get_' tools, but the resource specificity is clear. The description avoids tautology by not just repeating the tool name.

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 are multiple sibling tools for retrieving time-related data (get_time_entry_by_id, get_time_entries), but the description doesn't indicate this is for listing/filtering multiple entries versus getting a single entry. No context about prerequisites, typical use cases, or exclusions 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 provided, the description carries the full burden of behavioral disclosure. It states it's a read operation ('Get'), implying safety, but lacks details on authentication needs, rate limits, error handling (e.g., invalid ID), or response format. For a tool with zero 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, front-loaded sentence with zero waste—it directly states the tool's purpose without unnecessary words. Every part of the sentence ('Get a specific time entry by ID') contributes essential information, making it highly efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete for a tool with parameters. It doesn't explain return values, error conditions, or behavioral traits like idempotency. While the purpose is clear, the lack of context for usage and behavior makes it inadequate for safe and effective tool invocation by an AI agent.

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 both parameters (id and expand). The description adds no additional meaning beyond implying 'id' is required for retrieval, which is already clear from the schema. Baseline 3 is appropriate as the schema does the heavy lifting, but the description doesn't compensate with extra context like examples for 'expand'.

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

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

The description clearly states the action ('Get') and resource ('a specific time entry by ID'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'get_time_entries' (plural) by specifying retrieval of a single entry via ID. However, it doesn't explicitly contrast with other 'get_by_id' tools (e.g., get_contact_by_id), which slightly limits differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_time_entries' for listing multiple entries or clarify prerequisites (e.g., needing a valid time entry ID). Usage is implied from the name 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 states the action ('Get') but doesn't describe what 'Get' entails—whether it's a read-only operation, what data is returned, error handling for invalid IDs, or any rate limits. The description is too minimal to provide adequate behavioral context for a tool with potential side effects or constraints.

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 with no wasted words. It's front-loaded with the core purpose, making it easy to scan and understand quickly. Every word contributes directly to stating what the tool does.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what data is returned, error conditions, or behavioral aspects like read-only nature. For a tool that likely returns user details, more context is needed to help an agent use it effectively without trial and error.

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 both parameters ('id' and 'expand'). The description doesn't add any parameter-specific details beyond what's in the schema, such as examples for the 'expand' parameter or ID format constraints. This meets the baseline score when schema coverage is high.

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 ('a specific user by ID'), making the purpose immediately understandable. It distinguishes from sibling tools like 'get_users' (which retrieves multiple users) by specifying retrieval of a single user. However, it doesn't explicitly mention what 'get' entails (e.g., retrieving user details), 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. It doesn't mention sibling tools like 'get_users' for listing multiple users or 'get_user_by_id' versus other 'get_*_by_id' tools for different resource types. There's no context about prerequisites, authentication needs, or error 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 provided, the description carries full burden for behavioral disclosure. While 'Retrieve' implies a read operation, it doesn't mention pagination behavior (implied by skip/top parameters), rate limits, authentication requirements, or what format the results will be returned in. The description is minimal and lacks important operational context.

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 - a single sentence that states the core purpose without any fluff. It's front-loaded with the essential information and wastes no words, though this conciseness comes at the cost of 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?

For a tool with 7 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'users' means in this context, what fields are returned, how results are structured, or provide any examples. The minimal description leaves too much undefined for a tool with this complexity.

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 detailed parameter documentation, so the baseline is 3. The description adds no additional parameter context beyond what's already in the schema properties, but doesn't need to since the schema is comprehensive.

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 resource ('all users from TimeChimp'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'get_user_by_id' or explain what 'all users' means in context of the filtering parameters available.

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 'get_user_by_id' or other get_* tools. There's no mention of prerequisites, typical use cases, or when this bulk retrieval approach is preferred over individual lookups.

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. 'Update an existing contact' implies a mutation operation, but it doesn't disclose any behavioral traits such as required permissions, whether changes are reversible, rate limits, or what happens to fields not specified in the update. This leaves significant gaps for an agent to understand the tool's 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 with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place in conveying the basic purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.