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. '创建新的工作项' implies a write operation (creation), but it doesn't disclose any behavioral traits such as required permissions, whether the operation 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 phrase '创建新的工作项', which is extremely concise and front-loaded with the core action. There is no wasted language or unnecessary elaboration, making it efficient for quick understanding by an AI agent.

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

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

Given the complexity of a creation tool with 5 required parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the return values, error conditions, or behavioral aspects like side effects. While the schema covers parameters well, the overall context for safe and effective tool invocation is lacking, especially for a mutation operation.

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 semantics beyond what the input schema provides. However, schema description coverage is 100%, with all parameters clearly documented in the schema (e.g., 'priority' with optional values, 'type' with enum-like descriptions). This meets the baseline of 3, as the schema does the heavy lifting, but the description doesn't compensate with additional context like default values 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 '创建新的工作项' (Create new work item) clearly states the verb 'create' and the resource 'work item', which is specific and unambiguous. It distinguishes from siblings like 'delete_issue' or 'list_issues' by indicating creation rather than deletion or listing. However, it doesn't explicitly differentiate from 'create_project', which creates a different resource type, so it's not a perfect 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing project), exclusions, or comparisons to siblings like 'create_project' for creating projects instead of issues, or 'list_issues' for viewing existing ones. This leaves the agent without context for tool selection.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While '创建新项目' (create new project) implies a write/mutation operation, the description doesn't disclose any behavioral traits: no information about permissions required, whether creation is reversible, rate limits, error conditions, or what happens after creation. This is a significant gap for a creation tool with zero annotation coverage.

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

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

The description is a single, efficient sentence that states the core purpose without any wasted words. It's appropriately sized for a creation tool and gets straight to the point with 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 creation tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what a 'project' represents in CODING DevOps, what happens after creation, error scenarios, or provide any context about the system. The agent would need to guess about the tool's behavior and outcomes based solely on the name and parameter schema.

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 5 parameters thoroughly with descriptions and enums. The description adds no parameter information beyond what's in the schema - it doesn't explain relationships between parameters, provide examples, or add context about how parameters interact. Baseline 3 is appropriate when the schema does all the heavy lifting.

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

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

The description clearly states the action ('创建新项目' - create new project) and specifies the context ('在 CODING DevOps 中' - in CODING DevOps), which provides a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'create_issue' or explain what distinguishes a project from other entities in the 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 on when to use this tool versus alternatives. There's no mention of prerequisites, when to choose this over other creation tools like 'create_issue', or any context about project lifecycle management. The agent must infer usage from the tool name 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 full burden for behavioral disclosure. '删除' (delete) implies a destructive mutation, but the description doesn't specify whether deletion is permanent, requires specific permissions, has confirmation steps, or what happens to related data. This is inadequate for a destructive operation 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 just three characters in Chinese ('删除工作项'), which translates to 'delete work item'. It's front-loaded with the core action and resource, with zero wasted words. This is appropriate conciseness for a simple tool.

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

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

Given this is a destructive mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what constitutes successful deletion, error conditions, return values, or system behavior. For a tool that permanently removes data, this level of documentation is insufficient.

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

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

Schema description coverage is 100%, with both parameters (issueCode and projectName) documented in the schema. The description adds no additional parameter information beyond what the schema provides. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description.

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

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

The description '删除工作项' (delete work item) states a clear verb+resource action, but it's vague about what constitutes a 'work item' and doesn't distinguish from sibling tools like delete_project. It's better than a tautology but lacks specificity about the resource being deleted.

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 delete_project or list_issues. The description doesn't mention prerequisites, conditions for successful deletion, or what happens after deletion. It's a basic statement with no 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?

No annotations are provided, so the description carries the full burden. It states the tool deletes a project, implying a destructive mutation, but doesn't disclose critical behavioral traits: whether deletion is permanent, if it requires specific permissions, what happens to associated resources, or error conditions. 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, efficient sentence in Chinese that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with zero waste.

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

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

Given the tool's destructive nature, lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like irreversibility, permissions, or response format. For a mutation tool with high complexity (deletion), more context is needed to ensure safe and correct usage.

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

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

Schema description coverage is 100%, with the single parameter 'projectId' documented in the schema as '要删除的项目ID' (project ID to delete). The description adds no additional parameter semantics beyond this, but with only one parameter and full schema coverage, the baseline is high. No extra value is provided, but the schema suffices.

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 ('删除' meaning delete) and the resource ('CODING DevOps 中的指定项目' meaning specified project in CODING DevOps). It distinguishes from siblings like 'delete_issue' by specifying the resource type. However, it doesn't explicitly contrast with other project-related tools like 'create_project' or 'list_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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., project must exist), consequences (e.g., irreversible deletion), or when to choose 'delete_project' over other project operations like 'list_projects' for verification. The context is implied but not explicit.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only operation ('查询' means query) and mentions a default limit, but fails to detail critical aspects such as authentication needs, rate limits, pagination behavior, or what 'recently updated' means (e.g., time frame). This leaves significant gaps for a tool with multiple parameters.

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

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

The description is concise and front-loaded, stating the core purpose in the first clause. It uses two sentences efficiently to cover filtering and the default limit, with no wasted words. However, it could be slightly more structured by explicitly separating purpose from parameters.

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 (3 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits (e.g., authentication, error handling), output format, and comprehensive usage guidelines. While the schema covers parameters, the overall context for effective tool invocation is insufficient.

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

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

Schema description coverage is 100%, so the schema already documents all parameters (issueType, limit, projectName) with descriptions and required status. The description adds marginal value by reiterating the default limit and filtering capability, but doesn't provide additional syntax, format details, or contextual meaning beyond what's in the schema.

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

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

The description clearly states the tool's purpose: '查询我最近更新的工作项' (query my recently updated work items). It specifies the verb (query) and resource (recently updated work items), making the function understandable. However, it doesn't explicitly differentiate from siblings like 'list_projects' or 'create_issue', which would require a 5.

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

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

The description provides minimal guidance: it mentions filtering by IssueType and a default limit of 20, but offers no explicit advice on when to use this tool versus alternatives like 'list_projects' or 'create_issue'. There's no mention of prerequisites, exclusions, or comparative contexts, leaving usage ambiguous.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool queries project lists, implying a read-only operation, but doesn't disclose any behavioral traits such as authentication requirements, rate limits, pagination, error handling, or what the return format looks like (e.g., list structure, fields included). For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves beyond basic purpose.

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 any wasted words. It is appropriately sized and front-loaded, making it easy to parse quickly. Every part of the sentence contributes essential information (verb, resource, scope), earning its place.

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

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

Given the tool's complexity (a query operation with 1 parameter), lack of annotations, and no output schema, the description is incomplete. It covers the basic purpose but fails to address behavioral aspects (e.g., authentication, response format) or usage guidelines. For a tool with no structured data beyond the input schema, more context is needed to ensure the agent can use it effectively.

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

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

The input schema has 1 parameter with 100% description coverage ('项目名称，支持模糊匹配' - project name, supports fuzzy matching). The description adds no additional meaning beyond what the schema provides, as it doesn't mention parameters at all. With high schema coverage, the baseline is 3, as the schema adequately documents the parameter, but the description doesn't compensate or enhance understanding.

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: '查询当前用户在 CODING DevOps 中的项目列表' (Query the current user's project list in CODING DevOps). It specifies the verb '查询' (query) and resource '项目列表' (project list), and identifies the scope as '当前用户' (current user) in 'CODING DevOps'. However, it doesn't explicitly differentiate from sibling tools like 'list_issues' or 'create_project', which would require mentioning it's for listing projects specifically, not issues or creating 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_issues' (for listing issues) or 'create_project' (for creating projects), nor does it specify prerequisites, exclusions, or contexts for usage. The agent must infer usage from the purpose alone, which is insufficient 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.