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

No annotations are provided, so the description must convey behavioral traits. It discloses the dryRun default and its effect (return plan vs. actual write). It does not mention authentication requirements, idempotency, error behavior, or rate limits. The description adds minimal value beyond the schema, which already describes dryRun in detail.

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

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

The description is a single sentence that conveys the core purpose and a key behavioral note (dryRun default). It is extremely concise with no extraneous content.

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

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

Given 7 parameters, no output schema, and no annotations, the description is somewhat thin. It covers the main action and the important dryRun behavior but lacks information about return values, prerequisites (e.g., authentication), and error handling. It is adequate but not comprehensive.

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

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

Schema coverage is 71% (5 of 7 parameters have descriptions). The description adds that the tool works 'by number or work item ID', which summarizes the identifier and workItemId parameters but does not provide new information beyond the schema. The missing parameter descriptions (projectId, projectIdentifier) are not addressed. Thus, marginal added 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 that the tool adds comments to PingCode bugs or requirements using either a number or work item ID. It differentiates from sibling tools like pingcode_get_work_item or pingcode_create_work_item by specifying the exact action (adding a comment) and the target types (bugs/requirements).

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 explicitly mentions the default dryRun=true, indicating that by default no comment is actually added, guiding the agent to set dryRun=false for actual writes. However, it does not explicitly state when not to use this tool or mention alternatives like pingcode_list_work_item_comments for reading.

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?

Discloses that the tool does not read browser cookies/storage, saves user token to a local file with 0600 permissions, and explains the two-step flow. With no annotations provided, the description carries full burden and covers key behaviors.

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?

Description is concise and front-loaded, stating the purpose first then detailing the two scenarios. Every sentence adds value 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 one optional parameter and no output schema or annotations, the description adequately covers the tool's behavior for both input cases. It could optionally mention the structure of the returned current user object.

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?

Input schema has 100% coverage for the single 'code' parameter. Description adds meaning by explaining the two modes (with/without code) and what the code represents, going beyond the schema description.

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

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

Description clearly states the tool is for user-space browser authorization login, using specific verb (login) and resource (PingCode user auth). It distinguishes from siblings like pingcode_auth_status and pingcode_auth_logout by focusing on the login step.

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?

Description explains two usage modes: without code to get authorization URL, with code to complete login. It also warns not to paste web login token. However, it doesn't explicitly mention when to use alternatives like auth_status.

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

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

No annotations are provided, so the description carries the full burden. It discloses the destructive action of deleting a token file with permission 0600, which is transparent. It could be improved by noting the effect on the authenticated session, but it is adequately transparent for a logout 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 sentence with no wasted word. It is front-loaded with the action verb, making the purpose immediately clear. Every part 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 no parameters and no output schema, the description covers the essential information. It could be more complete by mentioning that this ends the authenticated session, but it is sufficient for a simple logout 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 tool has no parameters, so the schema already fully defines the interface. The description does not need to add parameter semantics, and it appropriately omits any. Baseline 4 for zero parameters.

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: clearing the locally saved user state token by deleting a specific file (0600 token file). This verb-resource combination is specific and distinguishes it from sibling tools like 'pingcode_auth_login' and 'pingcode_auth_status'.

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

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

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing to be logged in, or that it will end the authenticated session. The context of use is only implied.

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

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

With no annotations, the description carries the full burden. It discloses what is returned and explicitly states it does not return any token, which is a safety note. It lacks detail on side effects or permissions, but for a read-only status check, this is adequate.

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

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

The description is a single, front-loaded sentence that conveys all necessary information without redundancy. Every word 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 no output schema, the description fully explains the return values (mode, authorization status, expiration seconds, current user). For a simple tool with no parameters, this is complete.

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

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

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

The description clearly states the tool's purpose: querying authentication status, including mode, authorization status, expiration seconds, and current user. It distinguishes itself from siblings like pingcode_auth_login and pingcode_auth_logout by specifying it does not return tokens.

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

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

The description implies usage for checking auth status but provides no explicit guidance on when to use this tool versus alternatives. No exclusions or context for when not to use it.

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

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

No annotations are provided, so the description carries the full burden. It discloses that dryRun=true by default (safety) and that each field change triggers a separate bulk PATCH. However, it lacks explicit details on authorization needs, rate limits, or reversibility of changes.

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

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

Two sentences, front-loaded with purpose, followed by key behavioral details. Every part serves a function; no wasted words.

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

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

For a 10-parameter tool with no output schema, the description covers the bulk operation pattern, dry run, and field-level updates. It could note return format or error handling but is sufficient for agent decision-making.

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

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

Schema coverage is 100% with all parameters described. The description adds value by explaining overarching behavior (dryRun default, field-level PATCHes, expectedCurrentStatusName role) beyond individual parameter descriptions.

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

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

The description clearly states it's for bulk updating work items (priority/assignee/status) using the native bulk endpoint, differentiating it from single-update siblings like pingcode_update_bug_status.

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

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

The description explains dryRun default and expectedCurrentStatusName, but does not explicitly state when to use this tool versus alternatives like single-update tools. Usage guidance is implied rather than explicit.

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

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

No annotations are provided, so the description carries the full burden. It states the tool 'checks' configuration, but does not disclose whether it has side effects, requires authentication, or has any rate limits. It only describes what it returns, not behavioral traits.

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

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

A single sentence that efficiently conveys the tool's functionality. No wasted words, front-loaded with the action 'check' and then the output details.

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

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

The description explains what the tool returns (info to ask, where to find, env template), which is adequate for a setup check tool with no output schema. It could be slightly improved by mentioning if it also validates current environment variables, but it is already fairly complete.

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

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

The tool has no parameters (0 params). Per guidelines, baseline is 4. The description adds value by explaining the output (user guidance, location info, env template) beyond the empty schema.

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

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

The description clearly states the tool's purpose: to check PingCode MCP configuration completeness and return guidance on what to ask the user, where to find information, and env config template. It is distinct from sibling tools which focus on auth, bugs, requirements, etc.

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

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

While the tool's purpose implies it should be used for initial setup or troubleshooting, the description does not explicitly state when to use it, when not to use it, or suggest alternatives. Usage guidelines are implied but not 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. It discloses the key behavioral trait: default dryRun=true only returns a creation plan, and false actually creates. It also warns about statusName causing validation failures. This is transparent but could be improved by noting permissions or irreversible actions when dryRun is false.

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

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

The description is a single sentence, extremely concise, and front-loaded with the core purpose. Every phrase adds necessary information 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 (11 parameters, many siblings) and no output schema, the description covers the essential behavioral and parameter information. It mentions the dry run output ('仅返回创建计划'), which partially describes the return value, but a more explicit output structure would improve completeness.

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

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

The schema provides full descriptions for all 11 parameters (100% coverage). The description adds value by summarizing the required/optional fields, the default dryRun, and the recommendation for statusName. This helps the agent prioritize the most important parameters.

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 that the tool creates a single bug or requirement ('创建单个缺陷/需求'), specifying the action and resource. It highlights the required title and optional fields, and the default dryRun behavior, making the purpose unmistakable.

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

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

The description explains that by default dryRun=true returns only a plan, guiding users to use false for actual creation. It advises against passing statusName to avoid validation errors. However, it does not explicitly mention when to use this tool over siblings like pingcode_update_work_item_fields or pingcode_import_bugs.

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

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

The description explicitly states the tool is read-only ('只读'), which is critical behavioral info. Without annotations, this disclosure ensures the agent knows it is non-destructive. However, it lacks other behavioral details such as authentication requirements or rate limits.

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 conveys the core purpose without any wasted words. It is appropriately sized for the tool's simplicity.

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?

While the description is sufficient for a basic retrieval tool with no parameters and no output schema, it does not describe the structure or contents of the returned team information. Providing context about the response would enhance completeness.

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

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

There are no parameters, so the description adds no further meaning beyond the schema. The schema coverage is 100% by default, meeting the baseline for zero-parameter tools without requiring supplementary explanation.

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 retrieves current PingCode enterprise/team information and specifies it is read-only. The title reinforces the purpose, and it is distinct from sibling tools like pingcode_get_team_members which focus on member details.

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. While its simplicity (no parameters) reduces ambiguity, explicit context about its role among other team-related tools would improve decision-making for an AI agent.

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

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

With no annotations, the description carries the burden. It discloses read-only nature and fallback behavior. Could mention output format, but for a simple getter this is sufficient.

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

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

Two concise sentences, front-loaded with purpose. Every sentence adds value.

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

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

For a zero-parameter, no-output-schema tool, the description explains the essential behavior and edge case. Complete for its 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?

No parameters, so schema coverage is perfect. Description has no need to add param info, baseline score applies.

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

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

The description clearly states it retrieves the current user and explains a key behavioral detail: under client_credentials it returns the default user. This distinguishes it from sibling tools like pingcode_auth_status.

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

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

The description implies when to use (to get current user) but does not explicitly contrast with alternatives. The fallback scenario provides context for an edge case.

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 behavioral disclosure burden. It declares read-only ('只读'), aggregation, grouping by status, deduplication, and default assignee override. It does not detail pagination behavior or error conditions, but the key behavioral traits are covered.

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

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

Two concise sentences with no filler. Every sentence adds value: main aggregation logic, filtering options, and read-only declaration. Front-loaded with 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 tool with 8 optional parameters and no output schema, the description explains grouping, deduplication, filtering, and read-only nature. It lacks explicit mention of pagination (though pageSize parameter exists) and return format beyond 'groups with counts'. Still fairly complete given schema coverage.

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 88%, so parameters are already well-documented. The description reinforces the role of assigneeName and filter parameters but does not add significant new semantic meaning beyond what the schema provides. 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?

Description clearly states the tool aggregates bugs and requirements of the current assignee, groups by status with counts, and deduplicates. It specifies verb '聚合' (aggregate), resource '当前负责人的缺陷与需求' (bugs and requirements of current assignee), and filtering options, distinguishing from sibling tools like pingcode_list_my_bugs which likely provide raw listings.

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?

Description mentions filtering by assignee name, status, and update time, and that the tool is read-only. However, it does not explicitly state when to use this tool versus alternatives like pingcode_list_my_bugs or pingcode_search_work_items, nor does it provide when-not-to-use guidance. The use case is implied but not contrasted.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool gets configurations but does not indicate whether it is read-only, requires authentication, or has side effects. Important behavior like potential data fetching latency or lack of modifications is not mentioned.

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 short sentence, making it concise. However, it lacks front-loading of key information; for instance, the purpose is clear but parameter details are missing. Every sentence earns its place, but additional structured information would improve it without losing 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?

Given the tool has 4 parameters, no required fields, no output schema, and no annotations, the description should provide more details about usage context, expected output, and parameter behavior. The current description is too minimal to guide an AI agent effectively in selecting and invoking this tool over its many siblings.

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 4 parameters (kind, typeId, projectId, projectIdentifier) with 0% schema description coverage. The description provides no explanation of these parameters, their roles, or how they relate to the configuration retrieval. This is a critical gap for an AI agent to invoke the tool correctly.

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 retrieves project configurations (project, work item type, status, priority, members) for confirming Bug/requirement mapping. The verb '获取' (get) and resource 'project schema' are specific, but it does not explicitly differentiate from sibling tools like pingcode_list_bugs or pingcode_get_work_item.

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 phrase '用于确认 Bug/需求映射' indicates the tool is used to confirm mappings, providing some context. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., before creating or updating work items), and does not mention prerequisites or when not to use it.

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

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

With no annotations, the description provides 'read-only' context, but does not disclose permission requirements, rate limits, or side effects. This is adequate for a simple list 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?

A single, dense sentence efficiently conveys the tool's purpose, read-only nature, and key features (filtering, department ID limit, pagination). No superfluous content.

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

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

The description covers input filtering and pagination but omits output details. Given no output schema, a brief note on the returned data structure would improve completeness.

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

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

Schema description coverage is 50%; the description mentions filtering by keyword and department ID and pagination, adding some context beyond schema. However, pageSize and pageIndex lack descriptions in both schema and tool 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 clearly states the tool queries an enterprise member list and is read-only. It does not explicitly differentiate from sibling tools, but the purpose is distinct from work-item-related siblings.

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

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

No guidance on when to use this tool versus alternatives like get_current_user or get_current_team. The description lacks context for optimal usage and exclusions.

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

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

No annotations provided, so description carries full burden. It does not disclose authentication needs, error behavior, or what happens if identifier is invalid. It only mentions optional comments and image inclusion, but lacks other behavioral traits.

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 that front-loads the key action and optional features. No wasted words.

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

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

With 7 optional parameters and no output schema, the description should clarify usage context, such as how identifier and workItemId relate, or the role of projectId and projectIdentifier. The current description omits these, leaving gaps for a comprehensive understanding.

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

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

Schema coverage is 100% with detailed parameter descriptions. The description adds a summary of the tool's purpose (getting full details with optional comments) but does not provide additional meaning beyond what the schema already states.

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 specifies the exact action (get complete details of a single bug/requirement) and resource (work item), with optional comments. It contrasts with sibling tools like pingcode_list_bugs which list multiple items, and pingcode_search_work_items for search.

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 vs alternatives such as pingcode_list_work_item_comments for comments or pingcode_search_work_items. No when-not-to-use or prerequisite 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?

No annotations provided, and description only mentions default dryRun=true. Does not disclose side effects, permissions, or error behavior for a mutation 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?

Very concise single sentence, but lacks structure and key details. Not optimally informative for a complex import 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?

Incomplete for a 7-parameter import tool with no output schema. Missing details on behavior, return values, and prerequisites.

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

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

Schema coverage is 43%, but description adds no meaning beyond the schema. Does not explain mode, maxRows, projectId, projectIdentifier, or sheetName.

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?

Description clearly states the tool imports bugs from .xlsx/.csv files, distinguishing it from list/update tools. However, the phrase '按截图表头' is ambiguous and not explained, reducing clarity.

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

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

No guidance on when to use this tool versus alternatives like pingcode_import_requirements or pingcode_create_work_item. Missing context for 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 provided, so the description carries full burden. It only mentions the dryRun default but does not disclose other behaviors like error handling, required permissions, or side effects of import (e.g., whether it modifies existing 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 short and to the point, with no wasted words. It conveys the core purpose and default behavior efficiently.

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 information on return values, error responses, and how the import processes data (e.g., handling of duplicates or invalid rows).

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 low (43%), and the description does not add meaning beyond what the schema provides. It does not explain the mode, maxRows, projectId, or projectIdentifier parameters. The mention of '按截图表头' hints at column mapping but is insufficient.

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 action (import requirements from .xlsx/.csv) and the default dryRun mode. It clearly identifies the resource (requirements) and distinguishes it from sibling tools like pingcode_import_bugs, though not explicitly differentiated.

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

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

No guidance on when to use this tool versus alternatives (e.g., pingcode_import_bugs). No mention of prerequisites or when not to use it.

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?

Given no annotations, description carries full burden. It discloses the dryRun default behavior and that relationType can be custom. However, it omits side effects, error handling, permission requirements, or what happens if the relationship already exists.

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?

Extremely concise: two sentences front-load the core action. Every sentence adds meaningful information with no 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?

Does not explain the overall flow (how to identify source/target), the meaning of 'plan' in dryRun, expected response fields, or error cases. For a tool with 9 parameters, this is insufficient without output schema or more details.

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

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

Schema coverage is 100%, so baseline is 3. Description adds minimal value beyond what schema already provides (e.g., dryRun default, relationType options). It restates existing parameter descriptions without new insight.

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?

Description clearly states the action: linking two work items with a relationship types such as block, blocked_by, duplicate, etc. It specifies the core function, but does not differentiate from sibling tools like pingcode_unlink_work_items or pingcode_list_work_item_relations.

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. The description mentions dryRun default and relationType support, but does not address prerequisites, typical use cases, or when to prefer other linking tools.

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

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

No annotations, so description carries full burden. It adds the default project context but does not disclose pagination behavior, return format, or that filtering parameters (like stateNames, assigneeNames) are available. Behavior is partially transparent.

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

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

Single concise sentence front-loaded with the action. No wasted words, but could include a bit more detail (e.g., pagination) without losing 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?

Despite high schema coverage, the description lacks essential behavioral context for a list tool with 9 parameters and no output schema. It does not explain return format, pagination (pageSize/pageIndex), or how filters interact. Incomplete for an agent to use 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 high (78%), so baseline is 3. The description adds no extra meaning to any parameter beyond what the schema already provides (e.g., default project mention is not a parameter). No added 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 fetches a list of bugs with a default project 'PROJ', distinguishing it from sibling tools like pingcode_list_my_bugs (my bugs) and pingcode_list_requirements (requirements). The verb '拉取' and resource '缺陷列表' are specific.

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?

Only mentions default project 'PROJ', implying usage for that project but no explicit guidance on when to use vs siblings like pingcode_list_my_bugs or pingcode_search_work_items. No when-not-to-use or alternatives provided.

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

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

No annotations provided, and description does not mention read-only nature, side effects, or auth requirements. Assumes non-destructive but not explicit.

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?

Extremely concise – two sentences with no waste. Front-loaded with purpose immediately.

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 list tool with 9 parameters and no output schema, description only covers assignee default. Missing context on pagination, filtering, and return format.

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

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

Schema has 78% coverage; description adds context for assigneeName by explaining default from PINGCODE_DEFAULT_ASSIGNEE_NAME. Adds value beyond 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?

Clearly states it lists PingCode defects assigned to the current user ('拉取当前使用者负责的 PingCode 缺陷'). Differentiates from sibling 'pingcode_list_bugs' which likely lists all bugs.

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?

Mentions default assignee from environment variable, implying use for viewing personal bugs. No explicit when-to-use vs alternatives or exclusions. Guidance is minimal.

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 burden. It explains the default assignee mechanism but does not disclose whether the operation is read-only, required authentication, or side effects.

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

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

The description is two concise sentences with no redundancy, effectively 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?

Despite having 9 parameters and no output schema, the description omits details about return format, pagination, error handling, or authentication, leaving the agent uncertain.

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 high (78%), and the tool description does not add significant meaning beyond what is already in the schema for the parameters.

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 that the tool lists PingCode requirements assigned to the current user, distinguishing it from generic list_requirements and list_my_bugs siblings.

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

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

The description implies usage for fetching the current user's requirements but does not explicitly provide when-to-use or when-not-to-use guidance compared to alternatives.

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

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

No annotations are provided, so the description carries full burden. It only states the basic action and default project, but does not disclose whether the operation is read-only, pagination behavior, or any side effects. The agent cannot infer safety or limitations.

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 one sentence. Every word adds value by specifying the action and default project. However, it could be slightly expanded without becoming verbose.

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

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

Given the tool has 9 parameters, no output schema, and no annotations, the description is insufficient. It does not explain returned data format, filter usage, or pagination. An AI agent would lack critical context for correct 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 coverage is high (78%), and the schema already explains most parameters. The description adds no additional meaning beyond the default project context. It neither contradicts nor enriches the schema, earning a baseline score of 3.

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

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

The description clearly states the tool fetches a list of PingCode requirements with a default project. It distinguishes from siblings like pingcode_list_bugs by specifying 'requirements' and from pingcode_list_my_requirements by implying a project-wide scope. However, it does not elaborate on the exact resource scope (e.g., all projects or just PROJ).

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 over alternatives like pingcode_list_my_requirements or pingcode_search_work_items. It does not mention exclusions or prerequisites. Usage context is implied but not explicit.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions no side effects, permissions, rate limits, or safety profile. Although it is a read operation, the description does not explicitly confirm this, leaving 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, concise sentence that front-loads the purpose with no wasted words. It efficiently conveys 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?

Despite having 5 parameters and no output schema, the description lacks information on return format, pagination, or parameter dependencies (e.g., need for at least one of identifier/workItemId). This leaves significant gaps for the 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 60% (3 of 5 parameters described). The description adds meaning for 'identifier' and 'workItemId' by stating 'by number or work item ID', but does not clarify 'kind', 'projectId', or 'projectIdentifier'. It compensates partially but not fully.

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 action: 'get PingCode bug/requirement comment list' with a specific verb (get) and resource (comment list). It distinguishes from sibling tools that list work items or add comments, indicating a unique function.

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, nor any exclusions or context. It simply states the function without directing the agent on appropriate use cases.

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

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It states the tool lists relations and returns fields, but omits whether it is read-only, required permissions, rate limits, or behavior when no relations exist. This leaves significant gaps for a safe 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 a single sentence that clearly conveys the core action, optional filter, and return information without any wasted words. It is appropriately sized and front-loaded.

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

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

With 6 parameters, no required fields, full schema coverage, no output schema, and no annotations, the description covers the main purpose but lacks completeness. It does not explain the priority between identifier and workItemId, nor what relationType values are available. Adequate but with noticeable gaps.

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

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

Schema coverage is 100% and all parameters have descriptions in Chinese. The description adds minimal extra meaning by summarizing the overall function and return, but does not explain parameter interactions (e.g., priority between identifier and workItemId) or valid values for relationType. 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 explicitly states the action (list), resource (work item relations), scope (all relations with optional filter by relationType), and return value (id and target work item). This clearly distinguishes it from sibling tools like pingcode_link_work_items and pingcode_unlink_work_items.

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 mentions filtering by relationType but does not provide explicit guidance on when to use this tool versus alternatives, such as when to prefer listing over linking/unlinking, or any prerequisites. 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?

With no annotations, the description carries full burden. It discloses key behaviors: default dryRun=true (no real changes unless false), and validation that current state is '新提交'. This is safety-critical and goes beyond a simple mutation statement. It lacks details on idempotency or error handling, but the core transparency is good.

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

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

Two sentences, no waste. The key information is front-loaded: purpose, default behavior, safety check. Every word serves a 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 batch update tool with 8 parameters and no output schema, the description covers the main purpose, default behavior, and a critical constraint (state validation). It does not explain error handling or partial failures, but it is sufficiently complete for typical 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 coverage is 75%, so the schema already describes most parameters. The description adds context by tying dryRun and expectedCurrentStatusName to the workflow (default dryRun, state check). It does not add new parameter-level details beyond what's in the schema, so 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 clearly states the tool batches update of bug status from '新提交' to '已修复', with a specific verb ('批量更新') and resource ('缺陷'). It distinguishes from sibling tools like pingcode_update_bug_status (single bug) and pingcode_bulk_update_work_items (generic) by focusing on a specific workflow: marking bugs fixed after fixing.

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 explicitly says when to use: after fixing bugs, to batch update status. It provides the default dryRun and state validation. However, it does not mention when not to use it or compare with alternatives for single updates. Still, the context is clear enough for the agent.

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, description carries full burden. It discloses read-only nature, non-validation of workflow, and that legality depends on actual PATCH, providing key 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?

Two sentences, front-loaded with '只读' (read-only). Every sentence is meaningful and concise.

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?

Adequate for a read-only plan tool with high schema coverage, but lacks description of return value structure since no output schema exists. Missing details on what the plan contains.

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 baseline is 3. Description adds no parameter-specific information beyond what schema already provides.

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?

Description clearly states it is read-only and returns a status change plan. It differentiates from write tools like pingcode_update_requirement_status, but does not explicitly distinguish from other read tools.

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

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

No guidance on when to use this tool versus alternatives (e.g., before updating status to check feasibility). The description implies context but does not explicitly state when or when not to use.

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 explains that results are deduped by ID and include per-type counts. But it does not disclose pagination behavior, rate limits, or performance implications, nor does it mention that it is read-only (though it's a search). With zero annotation support, a score of 3 is appropriate.

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 dense Chinese sentence that front-loads the purpose. It covers many parameters concisely, though it could be broken into multiple sentences for readability. It is not verbose, but structure could be improved.

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

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

Given no output schema, the description should explain return format more fully. It mentions 'merged results deduped by ID and totals per type' but lacks details like sorting, order, or field structure. For a search tool with 31 parameters, this is adequate but not complete.

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 94% (high), so baseline is 3. The description adds value by explaining that raw filters accept lists up to 20, that some filters merge with name-based ones, and the timestamp format. It also clarifies defaults (e.g., kinds default). This exceeds the schema alone.

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 this tool performs a unified search across defects and requirements ('跨缺陷与需求统一搜索'). It lists supported filters and explains the merged result with dedup and per-type totals. This distinguishes it from sibling tools like pingcode_list_bugs and pingcode_list_requirements which are type-specific.

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

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

The description implies usage when a cross-type search is needed ('跨缺陷与需求统一搜索') and when raw filters are required. However, it does not explicitly contrast with siblings or provide when-not-to-use 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, the description carries full burden. It discloses that changes are merged into one PATCH and dryRun defaults to true, but does not discuss permissions, atomicity, failure behavior, or other important behavioral traits.

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

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

The description is a single, well-structured sentence that front-loads the purpose and default behavior. No wasted words.

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

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

Given the tool has 12 parameters and no output schema or annotations, the description is too brief. It lacks explanation of return values, error conditions, and the interplay between parameters like stateId and statusName.

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

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

Schema coverage is 100%, so baseline is 3. The description summarizes key parameters (assignee, priority, status) but does not add meaningful nuance beyond what parameter descriptions already provide.

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

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

The description clearly states it is a one-stop triage tool that merges assignee, priority, and status changes into a single PATCH operation, and optionally adds a comment. This distinguishes it from sibling tools like pingcode_update_bug_status which handle single updates.

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

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

The description implies usage for combined updates but does not explicitly state when to use this tool versus siblings like pingcode_update_work_item_fields or pingcode_update_bug_status. No exclusions or alternatives are provided.

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

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

No annotations are provided, so the description must carry the burden. It discloses the dryRun default (safe by default) but does not describe what happens upon actual deletion (e.g., irreversibility, permissions needed, side effects). The description is insufficient for a destruction 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 very short (two sentences), concise, and front-loads the main action. It wastes no words, though it could be slightly more structured with bullet points for key behaviors.

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

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

With 7 parameters, no output schema, and no annotations, the description is too brief. It does not explain return values, how to use other parameters like projectId or workItemId, or the implications of dryRun=false. The context is incomplete for an agent to use the tool 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?

Schema coverage is 100% with descriptions for all parameters. The description adds little beyond the schema, only summarizing that relationId is from a sibling tool. Baseline 3 is appropriate since the schema already provides meaning.

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 specifies the action 'delete' and the resource 'relationship of a work item', which is clear. It also notes that relationId comes from a sibling tool, aiding understanding. However, it could be more explicit about the type of relationship.

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 mentions that relationId comes from pingcode_list_work_item_relations, implying a prerequisite. It also notes the default dryRun=true. However, it lacks explicit guidance on when to use this tool versus alternatives like 'link_work_items' or 'update_work_item_fields'.

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

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

With no annotations, the description must disclose behavioral traits. It only states the basic action, omitting details on destructiveness, permissions, side effects, or requirements for parameters like identifier or workItemId. The dryRun and expectedCurrentStatusName fields are not explained.

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. It is concise but could include more context without becoming verbose.

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 9 parameters, no output schema, and no annotations, the description is too minimal. It omits information about optional parameters, status update methods, and protection conditions, making it incomplete for 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 coverage is 78%, so most parameters are already described in the schema. The description adds minimal value beyond implying that identifier is a user-facing number and workItemId is internal. 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 clearly states the action (modify status), resource (bug), and identification method (by number or work item ID). It effectively distinguishes from sibling tools that update requirements or perform other operations.

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

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

The description provides no guidance on when to use this tool versus alternatives like pingcode_update_work_item_fields or pingcode_mark_bugs_fixed. It lacks explicit context for appropriate 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?

With no annotations, the description carries full burden for behavioral disclosure. It only states 'modify status' without detailing side effects, atomicity, authorization requirements, error states, or the PATCH nature (only implied in dryRun). The schema hints at dryRun and expectedCurrentStatusName, but the description does not integrate these.

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

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

The description is a single sentence with no extraneous words. It efficiently communicates the core action and key identifiers.

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 9 parameters, no output schema, and no annotations, the description is too brief. It fails to explain the status transition logic (e.g., stateId vs statusName precedence), error handling, or expected return values. For a complex update tool, this leaves significant gaps 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 78% (high), so baseline is 3. The description adds minimal extra meaning: it mentions identifier and workItemId as lookup methods but does not clarify the priority between stateId and statusName, or the role of comment and expectedCurrentStatusName beyond 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 modifies the status of a single requirement using a number or work item ID. It is specific about the action (update status) and the target object (requirement), effectively distinguishing it from sibling tools like pingcode_update_bug_status or pingcode_update_work_item_fields.

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

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

The description implies usage for updating requirement status but provides no explicit guidance on when to use this tool versus alternatives (e.g., pingcode_update_work_item_fields for non-status updates). No when-not-to-use or prerequisite conditions are mentioned.

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

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

With no annotations, the description carries full responsibility. It discloses key behaviors: default dryRun=true (safe), only PATCHes changed fields, and includes a weak idempotency guard via expectedCurrentStatusName. Missing details on permissions or error handling, but major traits are covered.

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

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

The description is a single, well-structured sentence that is front-loaded with the purpose and key behavioral traits. Every word is necessary and earned.

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 high complexity (13 parameters, nested objects, no output schema), the description covers the most critical behavioral context (dry-run, patch-only). It does not mention the return value or error cases, but the schema descriptions already provide substantial help.

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

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

Schema coverage is 100%, so the description need not repeat parameter details. It adds value by explaining the dryRun default and that only changed fields are patched, and notes workItemId priority over identifier. This goes beyond the schema.

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

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

The description explicitly states the tool edits work item fields such as title, description, priority, assignee, parent, and custom properties, and specifies it operates by identifier or internal ID. This clearly distinguishes it from sibling tools that update status or perform bulk operations.

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

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

The description implies usage by listing editable fields but does not explicitly contrast with alternatives like update_bug_status or bulk_update_work_items. The dry-run and patch-only behavior is noted, but guidance on when to choose this tool is absent.

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