Personio Recruiting Ops Plane

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

No annotations are provided, so the description must disclose behavioral traits. It mentions 'through the buyer's saved connection details' indicating authentication, but fails to note that this tool can perform destructive operations (e.g., POST, DELETE) or that the 'confirm' parameter is required for non-GET requests. The description does not adequately inform the agent about safety 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 a single sentence, front-loaded with the key idea. It avoids verbosity but could benefit from a brief note on when to use it. Nonetheless, it is appropriately sized for the tool's generic nature.

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, generic API access) and no output schema, the description should hint at the response format or how errors are reported. It does not. However, the presence of many sibling tools may partially compensate, making a score of 3 appropriate.

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 86% (6 of 7 parameters have descriptions), so the schema already does most of the work. The description adds no additional context beyond what is in the schema; for example, 'path' is described as 'Full URL or documented path' in both. With high coverage, the baseline is 3, and the description does not elevate it.

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 can be used for any documented Personio Recruiting Ops Plane endpoint, contrasting with sibling tools that target specific operations. It gives a specific verb ('use') and resource ('endpoint'), leaving no ambiguity about its purpose.

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 that this tool is for covering any documented endpoint not covered by specific siblings, but it does not explicitly state when to use it over alternatives or when not to use it. The absence of explicit guidance on context or prerequisites limits its helpfulness for an AI agent deciding between tools.

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

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

No annotations are provided, and the description only states 'Create,' which implies a mutation. It fails to disclose any behavioral traits such as required permissions, side effects, rate limits, or confirmation steps beyond the confirm parameter in the schema.

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

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

The description is a single sentence that is front-loaded and to the point. It efficiently conveys the main purpose, though it could include more detail without sacrificing 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 no output schema and generic parameter descriptions, the description should explain what the tool returns (e.g., the created application object) and any prerequisites (e.g., existing candidate/job). It does not, leaving the agent with insufficient context for a creation 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?

Schema coverage is 100%, but the parameter descriptions are generic (e.g., 'JSON request body for documented write operations') and do not explain what fields are needed for this specific tool. The tool description adds no parameter-specific context, so the agent must infer usage from generic 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 creates a Personio recruiting application and lists the sources (careers-site, referral, etc.), making the purpose understandable. However, it does not define what an 'application' is in this context or how it relates to candidates/jobs, leaving some ambiguity.

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

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

The description implies usage for creating applications from various intake workflows, but it does not specify when not to use this tool or provide alternatives. Given sibling tools like create_webhook, the differentiation is implicit but not explicit.

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

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

No annotations are provided, so the description must disclose behavioral traits. It does not mention side effects, authentication requirements, or whether the webhook is immediately active. The description is too sparse to inform an agent about 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?

The description is a single short sentence, which is concise but arguably under-specified for a tool with 6 parameters and complex nested objects. It minimally earns its place but could benefit from more information.

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

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

Given the absence of an output schema and annotations, plus the complexity of the input schema (6 parameters, nested objects), the description is insufficient to fully understand the tool's functionality and context. It lacks details about the webhook creation process and expected behavior.

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

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

The input schema has 100% description coverage for all parameters, so the baseline is 3. The tool description adds no additional meaning beyond what the schema provides, which is adequate but not extra.

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

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

The description clearly states 'Create a Personio webhook' with a specific verb and resource, distinguishing it from sibling tools like delete_webhook, get_webhook, and update_webhook. However, it lacks additional context about what a webhook is or its scope.

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

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

No guidance is provided on when to use this tool versus alternatives such as update_webhook or list_webhooks. The description does not mention prerequisites, typical use cases, 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 provided, the description carries full burden for behavioral disclosure. It fails to mention any side effects, required permissions, or whether the deletion is immediate. The tool name implies mutation, but no details are given.

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 but severely under-specified. A single sentence that merely restates the name does not earn the conciseness label; it sacrifices necessary detail.

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 absence of output schema, annotations, and any behavioral details, the description is grossly incomplete. An agent cannot determine how to safely or correctly invoke this tool based on the provided information.

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?

Although schema description coverage is 100%, all parameter descriptions are generic and not specific to delete_webhook. The description adds no meaning beyond the schema, failing to clarify which parameters (e.g., path_params) are necessary or how they relate to the deletion action.

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

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

The description 'Delete a Personio webhook' essentially restates the tool name 'delete_webhook', adding only the noun 'Personio'. This is a tautology that does not differentiate the tool from siblings like 'create_webhook' or 'update_webhook'.

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., update_webhook, get_webhook). There is no mention of prerequisites, such as needing a webhook ID, or when deletion is appropriate.

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

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

No annotations provided, so the description must disclose behavior. It only says 'Get one application' without mentioning read-only nature, authentication needs, error responses, or what happens with invalid IDs. The description is insufficient for the agent to understand side effects 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 short but the second sentence is a fragment ('Recruiting applications for...') and not a complete statement. It could be more concise and 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?

Given the complexity (5 parameters, nested objects, no output schema), the description lacks details about return values, how to use optional parameters, and typical usage patterns. The agent would need to rely heavily on the schema and context, which may be 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 80%, so baseline expectation is met. The tool description adds no additional meaning to parameters beyond what the schema already provides. Parameters like 'include' and 'query_json' are not explained 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 clearly states 'Get one application' and mentions the tool is for pipeline, stage, source, owner, and freshness analysis. It distinguishes itself from sibling list_applications by indicating it retrieves a single application, but could be more specific about the exact data returned.

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 list_applications or get_recruiting_job. No context about prerequisites or typical use cases, leaving the agent to infer usage.

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

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

No annotations are provided, and the description does not disclose behavioral traits (e.g., idempotency, side effects, auth requirements, or error behavior). The description is too minimal to inform an AI agent about what happens when the tool is invoked.

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 with two sentences, but the second sentence is redundant and confusing, reducing conciseness. The first sentence is properly front-loaded.

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

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

Given the tool has 5 parameters (including nested objects), no output schema, and many sibling tools, the description is too minimal. It does not explain parameter usage, response semantics, or how this tool fits into the recruiting workflow.

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 does not add any meaning beyond the input schema. The schema already covers 4 of 5 parameters with descriptions (80% coverage), but the description itself provides no parameter context or usage hints.

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?

First sentence clearly states 'Get one candidate', indicating the tool retrieves a single candidate record. However, the second sentence is confusing and unnecessary, and does not differentiate from siblings like list_candidates or get_application.

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 such as list_candidates or get_application. The description only states the basic action without context.

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

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

The description implies a read-only operation ('Show') with no destructive effects, which is appropriate. However, with no annotations, it lacks details about output format, limits, or any special 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 a single, concise sentence that front-loads the core purpose. It could be slightly more specific but is appropriately sized.

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 is adequate but leaves 'coverage' ambiguous. It could state that it returns a list of available capabilities. Overall, it provides minimal but essential context.

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

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

There are no parameters, and schema coverage is 100% (empty schema). The description adds no parameter info, but baseline 4 applies per instructions 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 states 'Show Personio Recruiting Ops Plane question, reporting, and action coverage,' which clearly identifies the verb 'Show' and the resource as coverage information about the Recruiting Ops Plane. It distinguishes from sibling CRUD tools, but 'coverage' is somewhat vague.

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 that it is for inspecting capabilities or provide any context about typical 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 must convey behavioral traits. It does not disclose whether the tool is read-only, what authentication is needed, or any side effects. The description is minimal and lacks 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?

Two concise sentences deliver the essential information without redundancy. 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?

The tool has 5 parameters and nested objects, but the description does not explain return values (no output schema) or how to use parameters like query_json. It feels incomplete for the complexity.

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

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

The schema already describes parameters with 80% coverage, including enums and types. The description adds no additional meaning, 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 action 'Get one jobs_catalog_item' and specifies the resource. It adds context 'Personio HRIS jobs catalog for cross-checking recruiting job metadata,' which distinguishes it from list operations like 'list_jobs_catalog'.

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 'for cross-checking' implies a usage scenario, but there is no explicit guidance on when to use this tool versus alternatives like 'list_jobs_catalog' or 'get_recruiting_job'. Prerequisites and conditions are not 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?

No annotations are provided, and the description does not disclose behavioral traits such as idempotency, side effects, permissions, rate limits, or return behavior. For a read operation, it does not confirm safety or idempotency, leaving the agent guessing about implications.

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 without waste. It is front-loaded with the key action. However, it could be slightly more informative while remaining concise, hence 4.

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 5 parameters, nested objects, and no output schema or annotations, the description is insufficient. It does not explain return values, error conditions, or usage context like pagination. The presence of sibling list_org_units suggests more contextual guidance is needed.

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

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

Schema description coverage is 80%, so the schema already explains most parameters. The tool description does not add significant meaning beyond the schema. It does not explain nested objects or additional properties in a way that compensates for the missing coverage, but baseline is 3 due to high schema coverage.

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

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

The description clearly states 'Get one org_unit', specifying the action and resource. It distinguishes from sibling list_org_units by emphasizing 'one'. It also explains that org units include departments and teams and are used for owner/function joins, providing context.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives like list_org_units. It mentions 'for owner/function joins' but does not specify scenarios or prerequisites. Lack of when-to-use or when-not-to-use instructions reduces usability.

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 only implies a read operation ('get') but lacks details on authentication, rate limits, or any side effects. The description does not mention that the tool is read-only or the impact of different parameter values.

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 brief (one sentence plus a fragment) and front-loaded with the purpose. However, the second part is slightly awkwardly phrased ('Personio persons for resolving...') and could be more 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?

With 5 parameters (including nested objects and enums), no output schema, and no annotations, the description is insufficient. It does not explain the response format, behavior differences based on detail_profile, or how to use path_params or query_json correctly.

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

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

Schema description coverage is 80% (high), so the baseline is 3. The description adds no additional meaning beyond the schema's parameter definitions; it does not explain how parameters like include, query_json, or detail_profile affect the result.

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 a single person from Personio and specifies its use case: resolving hiring-team person IDs from recruiting applications. This is specific and distinguishes it from sibling tools like list_persons.

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

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

The description provides context for use (resolving IDs from recruiting applications) but does not explicitly state when not to use it or suggest alternatives such as list_persons for multiple records or get_candidate for candidate data.

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, and the description does not disclose any behavioral traits beyond the implied read operation. It does not mention side effects, authentication needs, rate limits, or error handling for missing IDs.

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 with two sentences, front-loading the core purpose, and contains no unnecessary words or repetition.

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

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

Given the tool has 5 parameters, nested objects, and no output schema, the description is too minimal. It does not explain return values, error scenarios, or how 'function-level slicing' relates to usage, leaving 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 80% (4 of 5 parameters described), so the baseline is 3. The description adds no extra meaning beyond what's in the schema; the purpose is clear but parameter details come from 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 'Get one recruiting_category' and mentions its use for function-level slicing, which clearly distinguishes it from sibling tool 'list_recruiting_categories' that retrieves all categories.

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

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

The description provides no guidance on when to use this tool versus alternatives such as 'list_recruiting_categories' or other get tools. It lacks explicit when-to-use, when-not-to-use, or prerequisite 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 exist, and the description provides minimal behavioral context. It indicates a read operation implicitly but omits details on errors, side effects, or permissions. The second sentence about joins is vague and does not clarify behavior.

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

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

The description is short but the second sentence is poorly structured and unclear. It could be more concise without the confusing clause.

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 5 parameters and no output schema, the description fails to explain return values, error handling, or how to use optional parameters like include or query_json. The ambiguous second sentence does not fill the gap.

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 (80%), and schema already provides meaningful descriptions for most parameters. The description adds no extra parameter detail, 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 states 'Get one recruiting_job' clearly, indicating a single-record retrieval verb and resource. It distinguishes from sibling list_recruiting_jobs but the second sentence is confusingly phrased, reducing clarity slightly.

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 list_recruiting_jobs or other get_* tools. No mention of prerequisites or context for 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?

With no annotations, description carries full burden. Only states 'Get one webhook' and a domain limitation. No disclosure of read-only nature, authentication requirements, rate limits, or behavior on success/failure. Minimal behavioral insight provided.

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 redundancy. Efficiently conveys core purpose and a key limitation. Could be slightly more informative 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 5 parameters, no output schema, and no annotations, description is insufficient. Does not explain return format, error handling, or impact of parameters like 'include' or 'detail_profile'. Lacks completeness for effective tool use.

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

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

Schema description coverage is 80%, so baseline is 3. Description adds minor context about HRIS domain and recruiting events limitation but does not elaborate on parameter usage 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 states 'Get one webhook' and specifies domain (Personio HRIS) and limitation (Recruiting-domain events not available). Clearly distinguishes from sibling tools like list_webhooks or create_webhook. Missing explicit mention of retrieval by ID, but input schema makes that obvious.

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?

Implies usage for fetching a single webhook by ID, but no explicit guidance on when to use versus list_webhooks or other alternatives. The recruiting-domain limitation provides context but does not direct agent away from this tool in certain 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, and the description does not disclose behavioral traits such as read-only status, permissions, side effects, or rate limits. It only states the basic retrieval action, leaving the agent uninformed about important constraints.

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

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

The description consists of two concise sentences with no extraneous words. The key action is front-loaded ('Get one workplace'), and the second sentence adds valuable context 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 lack of an output schema, the description should explain what the tool returns. It does not mention return fields, pagination, or examples. With 5 parameters including nested objects and an enum, the description is too brief to provide adequate context for 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 80%, meaning most parameters have descriptions within the schema. The tool description adds no additional parameter details. According to the rubric, with high schema coverage, a baseline of 3 is appropriate even without extra parameter information 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?

Description clearly states 'Get one workplace' indicating a single retrieval operation. The additional context 'Workplaces for location/region slicing' explains the resource's purpose, distinguishing it from list_workplaces which retrieves multiple. However, it does not explicitly differentiate from other get_* sibling 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 explicit guidance on when to use this tool versus alternatives like list_workplaces. There is no mention of prerequisites, scenarios, or when not to use. The description implies use for fetching a single workplace by ID but does not state 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 are provided, and the description does not disclose behavioral traits such as pagination, rate limits, data freshness, or whether results are read-only. The schema hints at pagination, but the description omits this, leaving the agent uninformed about important behavioral aspects.

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 is front-loaded with the core purpose. It is efficient, though it could expand slightly to cover key usage details 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 complexity (11 parameters, no output schema, numerous sibling tools), the description is insufficiently complete. It lacks details on pagination, sorting, filtering syntax, and return value shape, which are critical 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?

With only 45% schema description coverage, the description adds modest context by mentioning filter dimensions (pipeline, stage, etc.), but does not explain the purpose of common parameters like page, cursor, sort, or query_json. The schema itself has some descriptions, but the description does not compensate adequately for the low coverage.

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

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

The description clearly states the tool lists applications, specifying it is for recruiting applications and mentions key filtering/analysis dimensions (pipeline, stage, source, owner, freshness). This distinguishes it from sibling tools like get_application (single) and list_candidates (different entity).

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

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

The description implies usage for pipeline, stage, source, owner, and freshness analysis, but does not explicitly state when to use this tool versus alternatives like search or get endpoints. No exclusion criteria or when-not-to-use guidance is provided.

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

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

Without annotations, the description carries the full burden of behavioral disclosure. It only mentions ordering ('ordered latest first') but fails to disclose other important behaviors like pagination, error handling, or the need for an application identifier.

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 concise with two sentences, but it is under-specified given the complexity of the tool. Conciseness should not come at the expense of necessary information.

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

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

Given the high parameter count (9), no output schema, and no annotations, the description is severely incomplete. It omits critical context such as required parameters (e.g., application ID), pagination behavior, error cases, and response structure.

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 (33%). The description does not add any meaning to the 9 parameters; it only says 'for one application' without specifying how that is parameterized. This fails to compensate for the schema's lack of documentation.

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

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

The description clearly states it lists 'application_stage_transitions' for one application, ordered latest first. It uses a specific verb and resource, and the constraint 'for one application' distinguishes it from general list tools like list_applications.

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 a single application's stage history but provides no explicit guidance on when to use this tool versus alternatives (e.g., list_applications or get_application). No when-not or alternative tools 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?

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states it lists candidates, with no mention of read-only nature, side effects, performance implications, or pagination behavior.

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

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

The description is very short (2 sentences), but the first sentence is a tautology of the tool name. While concise, it omits necessary details, making it under-specified rather than efficiently 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?

Given the tool has 9 parameters, nested objects, and no output schema, the description is severely lacking. It does not explain pagination, return structure, or how candidates relate to other entities, leaving agents underinformed.

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 only 33% (3 of 9 parameters have descriptions). The tool description adds no parameter meaning beyond what is in the schema, failing to compensate for the low coverage.

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

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

The description states 'List candidates' with a clear verb and resource. The second sentence adds context of recruiting, but does not distinguish from sibling tools like list_persons or list_applications, which could overlap.

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 candidate lookup, source analysis, and application joins, but provides no explicit guidance on when to choose this over alternatives, nor any exclusion criteria.

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

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

No annotations provided, and description does not disclose behavioral traits such as read-only nature, pagination, or rate limits. The description is too brief to cover these aspects.

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 short but not effectively informative; first sentence merely restates the name. Every sentence should add value, but this is under-specified.

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

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

With 9 parameters, no output schema, and no annotations, the description is incomplete. Lacks guidance on return values, pagination, and usage context.

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

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

Schema description coverage is only 33% (3 of 9 parameters have descriptions). The tool description adds no parameter details beyond schema. Baseline of 3 not achieved due to low coverage and lack of compensation.

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 states it lists a jobs catalog and mentions cross-checking, which gives some purpose but is vague and repetitive of the tool name. It does not clearly differentiate from sibling tool list_recruiting_jobs.

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 list_recruiting_jobs. No when-not or context 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 present, so the description carries full burden. It only says 'List org_units' without disclosing pagination behavior, sorting, filtering capabilities, or that it returns a list. The schema implies pagination and filtering, but the description fails to surface these 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 very concise at two sentences with no wasted words. It is front-loaded with the verb and resource. However, it could be slightly more structured (e.g., bullet points) to improve scanability, but it remains efficient.

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

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

Given the complexity (9 parameters, nested objects, no output schema, no annotations), the description is severely incomplete. It does not explain pagination, filtering, output format, or typical use cases. The tool is far more complex than what the description conveys.

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 only 33%, and the tool has 9 parameters. The description adds no parameter explanations beyond what the schema provides. For example, it does not clarify the meaning of 'include', 'query_json', or 'detail_profile' despite the schema having descriptions for some. This fails to compensate for low coverage.

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

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

The description clearly states 'List org_units' and explains what org units are (departments, teams) and their purpose ('for owner/function joins'). It is specific enough to distinguish from sibling tools like list_candidates or list_applications, but does not explicitly differentiate from get_org_unit.

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

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

The description provides no guidance on when to use this tool versus alternatives (e.g., get_org_unit). It lacks context on prerequisites, scenarios, or exclusions, leaving the agent to infer usage from the 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?

No annotations are provided, so the description carries full burden. It only says 'List persons' and does not disclose pagination, filtering, sorting, response format, or any behavioral traits beyond the trivial fact it lists persons.

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

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

The description is appropriately short (two sentences) and front-loaded with the verb+resource. However, it is so brief that it sacrifices valuable information that could be added without being 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's complexity (9 parameters, no output schema, nested objects), the description is far from complete. It lacks info on pagination, response structure, filtering, and other key aspects needed 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?

The description adds no parameter guidance, and schema coverage is only 33%. With 9 parameters, the description should help the agent understand which params to use and how, but it doesn't mention any 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 ('List persons') and the specific domain ('Personio persons for resolving hiring-team person IDs returned by recruiting applications'). This distinguishes it from sibling tools like get_person and list_candidates.

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

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

The description provides context for when to use the tool: for resolving hiring-team person IDs from recruiting applications. It does not explicitly state when not to use it or mention alternatives, but the purpose is clear enough.

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, and the description only says 'List' which implies a read operation but does not disclose behavioral traits like idempotency, authorization needs, rate limits, or side effects. It is insufficient for an AI agent to understand the tool's behavior beyond the basic action.

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

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

The description is very concise at two sentences, with no wasted words. It front-loads the core purpose. However, it could benefit from additional structured information, but for a simple list tool, it is appropriately sized.

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 9 parameters, no output schema, and no annotations, the description is severely lacking. It does not explain pagination, filtering, or what data is returned. The agent cannot determine how to use parameters like page, cursor, or query_json without external knowledge.

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 information about the 9 parameters beyond what is already in the input schema. With schema description coverage at 33%, some parameters are documented in the schema, but the tool description fails to compensate for the remaining parameters, leaving their semantics unclear.

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 'List recruiting_categories' with a specific verb and resource. It further clarifies that these are 'Recruiting job categories for function-level slicing,' which distinguishes it from other list_* sibling tools that list different entities like applications, candidates, or jobs.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as get_recruiting_category or list_recruiting_jobs. There is no mention of context, prerequisites, or exclusions.

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

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

With no annotations, the description carries full responsibility. It fails to disclose that this is a read-only operation, does not explain pagination behavior (cursor, limit), and omits details on the effect of the detail_profile parameter (though that is in the schema). It also does not mention authentication requirements, rate limits, or any 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 very short (two sentences) but the second sentence is a fragment that adds confusion rather than clarity. It is concise but at the expense of being informative. The structure could prioritize key details like pagination and filtering.

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 insufficient. It does not address pagination, filtering, or the difference between detail_profile values. The tool's complexity demands a more comprehensive description.

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 only 33%, but the description does not explain any of the parameters (page, sort, limit, etc.). It only vaguely alludes to the content of the list without clarifying how parameters affect results. The detail_profile description is in the schema but not reinforced in the 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 'List recruiting_jobs' clearly states the action and resource. However, the second sentence 'Recruiting jobs for opening inventory, category, department, and hiring-team joins' is ambiguous—it might describe the contents or filtering options, which undermines clarity. It does not sufficiently differentiate from sibling tools like get_recruiting_job or api_request.

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

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

No guidance is provided on when to use this tool versus alternatives such as get_recruiting_job for a single job or list_applications for applications. There is no mention of prerequisites, scenarios, or when to avoid this tool.

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 the 30-day time constraint but does not mention pagination, rate limits, or what happens if no activity exists. The 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?

Two concise sentences with no redundancy, though the first sentence ('List webhook_activity.') could be merged with the second. It is front-loaded but a bit too short.

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 lacks crucial context: no output schema, no explanation of pagination, filtering, or how to specify the webhook. For a tool with 9 parameters and no output schema, the description is significantly incomplete.

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

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

Schema coverage is low (33%), and the description adds no information about any of the 9 parameters (page, sort, limit, etc.). The description neither explains how to specify the webhook nor the meaning of the many filtering/pagination 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 verb 'List', the resource 'webhook_activity', and specifies the scope: 'delivery activity from the last 30 days for one webhook.' This distinguishes it from sibling tools like list_webhooks (list webhook definitions) and list_webhook_events (list event types).

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 that this tool is for a single webhook's activity within a time window, but it does not explicitly state when to use it instead of other tools, nor does it provide exclusion criteria or alternative recommendations.

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 it covers 'last 30 days' and 'for one webhook,' but lacks details on pagination, sorting, or other behaviors beyond what the input schema shows. No annotations to supplement.

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

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

Single sentence, front-loaded, no wasted words. However, given the tool complexity with 9 parameters, more structured information could improve clarity.

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

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

With 9 parameters, no output schema, and no annotations, the description is far too minimal. It does not explain return values, filtering, or pagination.

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 only 33%, and the description adds no explanation for the 9 parameters. It does not compensate for the low coverage.

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

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

Description clearly states it lists HRIS webhook event deliveries from the last 30 days for one webhook, distinguishing it from sibling tools like list_webhooks and get_webhook.

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

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

No explicit guidance on when to use this tool versus alternatives like list_webhook_activity or when not to use it. The context is implied but not 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 the full burden but only states the basic function. It does not disclose pagination behavior, authentication requirements, rate limits, or what data is returned (e.g., webhook IDs, URLs). This is insufficient for an agent to understand side effects or constraints.

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

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

Two concise sentences with no redundancy. The critical domain distinction (HRIS vs recruiting) is front-loaded. Every word adds value.

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

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

For a tool with 9 parameters, no output schema, and no annotations, the description is far too minimal. It does not explain how to paginate, what fields are returned, or how `path_params` or `include` are used. An agent cannot reliably use this tool without additional context.

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

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

Schema description coverage is 33%, meaning most parameters lack descriptions. The description adds no additional meaning beyond the schema, such as how `query_json` or `detail_profile` affect results. It does not compensate for the unannotated 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 tool lists webhooks for Personio HRIS delivery monitoring, and explicitly excludes recruiting-domain events. This distinguishes it from sibling tools like list_webhook_events and list_webhook_activity.

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_webhook, list_webhook_activity, or create_webhook. There is no mention of prerequisites or contexts where this tool is preferred.

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 must fully disclose behavioral traits. It only states a list operation, omitting details about pagination (cursor, page, limit), sorting, filtering, or that it is read-only. This is insufficient for an agent to understand the tool's behavior.

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

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

The description is only two sentences, which is concise but under-specified for a tool with 9 parameters and no annotations. It sacrifices necessary detail for brevity, making it less useful.

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 9 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to cover pagination, filtering, sorting, or return format, leaving the agent without sufficient context to use the tool correctly.

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

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

Schema coverage is 33% (only 3 of 9 parameters have descriptions). The description adds no parameter-level meaning beyond the schema, failing to compensate for the many undocumented parameters like page, sort, cursor, include, and per_page.

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

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

The description clearly states 'List workplaces' as the primary verb+resource. The phrase 'Workplaces for location/region slicing' adds a specific usage hint distinguishing it from other list_* siblings. However, it does not explicitly differentiate from get_workplace or other listing 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?

The description provides only implicit guidance through 'for location/region slicing'. It lacks explicit when-to-use or when-not-to-use instructions, and does not mention alternatives like get_workplace for a single workplace.

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, and the description does not disclose any behavioral traits such as idempotency, side effects, error conditions, or permissions required. The agent receives no information beyond the fact that it sends an event.

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, which is concise, but it is too terse to be helpful. It does not explain what a ping event is or provide any actionable detail, making it under-specified rather than efficiently informative.

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 6 parameters, no output schema, and many sibling tools, the description is extremely incomplete. It does not cover return values, required parameters, error handling, or the purpose of the ping, leaving the agent with minimal guidance.

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

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

Schema coverage is 100%, so the schema already describes each parameter. The description adds no additional meaning, but with high coverage the baseline is 3. The generic parameter names (e.g., 'path_params', 'body_json') are not elaborated for this specific tool.

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 a specific action ('Send a Personio webhook ping event') but does not clarify what a 'ping event' accomplishes or how it differs from sibling tools like 'redeliver_webhook_events' or 'list_webhook_events'. The verb+resource is clear but lacks context.

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

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

No guidance is given on when to use this tool versus alternatives. Sibling tools exist for creating, deleting, listing, and redelivering webhooks, but the description does not explain the specific use case for a ping.

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 lacks any behavioral disclosure (e.g., that this is a destructive or idempotent operation). Schema parameters confirm and dry_run suggest safety measures, but the description does not cover implications.

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 but lacks structure (no mention of prerequisites or output). It is front-loaded but omits critical guidance, so it is not well-balanced.

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 and a write operation, the description is too minimal. It does not explain the selection mechanism, the role of dry_run/confirm, return values, or error scenarios.

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, so the description need not add much. However, it adds no extra value beyond the schema (e.g., no explanation of how body_json relates to redelivery).

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 'Redeliver selected webhook events' uses a clear verb-resource pair, distinguishing it from sibling tools like list_webhook_events and ping_webhook. However, it does not specify how events are selected or what 'redeliver' entails.

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

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

No guidance is provided on when to use this tool vs alternatives (e.g., list_webhook_events for inspection). The schema hints at dry_run and confirm, but the description does not explain usage context.

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

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

No annotations are provided, and the description does not disclose any behavioral traits such as whether the update is idempotent, what side effects occur, or authorization requirements. This is a significant gap for a mutation 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, but it is under-specified rather than concise. It does not front-load key information or provide enough context for effective use. Every sentence should add value, and this one is too minimal.

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 the tool (6 parameters, nested objects, no output schema), the description is completely inadequate. It fails to explain the purpose of 'confirm' and 'dry_run', the expected structure of 'body_json', or how 'path_params' identifies the webhook. This is a critical omission.

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. The description adds no additional meaning to the parameters beyond what the schema already provides. It does not explain how 'body_json' or 'path_params' are used in the context of updating a webhook.

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 'Update a Personio webhook' uses a specific verb and resource, distinguishing it from siblings like create_webhook and delete_webhook. However, it lacks detail on what aspects of the webhook can be updated, making the purpose vague beyond the basic action.

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, no prerequisites, and no context about when not to use it. The user is left without information about required parameters or typical 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 must fully disclose behavior. It indicates a write operation but does not explain side effects, authentication requirements, or error states. The dry_run and confirm parameters are not explained in the description.

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 redundant information. It is front-loaded with the purpose and then the input method options.

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

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

Given the complexity (7 parameters, nested objects, conditional inputs) and no output schema, the description is too brief. It does not specify return values, mutual exclusivity of file_base64 and file_url, or behavior of confirm/dry_run.

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 baseline is 3. The description adds minimal value by restating that file_base64 or file_url can be used, but does not explain other parameters like confirm, dry_run, query_json, or headers_json.

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 (upload a document) and the resource (to Personio for a recruiting application), and specifies two input methods (base64 or URL). It distinguishes itself from sibling tools, as no other upload tool exists.

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 use when attaching a document to a recruiting application, but does not explicitly state when not to use it or mention alternatives. It provides input format guidance but lacks contextual usage scenarios.

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