Personio Recruiting Ops Plane

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

No annotations provided, and description fails to mention that non-GET methods require confirmation set to true, nor any authentication implications 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?

Single sentence is brief but adequate for a generic tool; however, it could be more informative without being wordy.

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 generic API tool with 7 parameters including confirm/dry_run flags and nested objects, the description is too sparse. Missing essential guidance on how to construct requests or interpret responses.

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 covers 86% of parameters with descriptions; the description adds no additional parameter context beyond the schema, so it meets the baseline.

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 'Use any documented endpoint' which clarifies it's a generic HTTP request tool, but the verb 'use' is vague. It distinguishes from sibling tools in that those are specific, but doesn't explicitly contrast.

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 mention of when to prefer specific tools over this generic one; no guidance on prerequisites or context for using 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?

No annotations provided. The description does not disclose behavioral traits like idempotency, side effects, authorization needs, or what happens to existing applications.

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 is concise but lacks structure and front-loading of critical 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?

With 6 generic parameters and no output schema, the description fails to explain return values, required body_json fields, or how to construct the request for this specific endpoint.

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?

While schema coverage is 100%, the parameter descriptions are generic (e.g., 'body_json' as 'JSON request body'). The tool description adds no specific meaning to these parameters for application creation.

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 source workflows (careers-site, referral, etc.), distinguishing it from sibling read tools like get_application or 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?

No guidance on when to use this tool vs alternatives, no prerequisites mentioned (e.g., candidate existence), and no when-not-to-use 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 the description says nothing about side effects, authorization needs, rate limits, or destructive nature. The agent has no behavioral insight.

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 at five words, but under-specified for a tool with six parameters. Lacks structure (e.g., no examples, no important notes).

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 six parameters, no output schema, and no annotations, the description is severely incomplete. It fails to cover return values, event types, or required context for webhook creation.

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 extra meaning beyond the schema; it does not explain parameter relationships or required combinations.

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 'Create a Personio webhook,' which is clear and uses a specific verb and resource. However, it does not differentiate this tool from siblings like update_webhook or delete_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 vs alternatives (e.g., update_webhook). No context on prerequisites 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 behavioral details beyond the schema. The description does not disclose side effects, authorization needs, or the role of confirm/dry_run parameters, despite no annotations.

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 is efficient, but it sacrifices completeness for brevity.

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

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

Description is too sparse given 6 parameters, no annotations, and no output schema. It fails to explain how to specify the webhook or the result of deletion.

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 adds no additional meaning to the parameters beyond what the 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 'Delete a Personio webhook' with a specific verb and resource, and it distinguishes from sibling tools like create_webhook, update_webhook, and list_webhooks.

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, no prerequisites or exclusions 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?

Annotations are absent, so the description carries full responsibility. It only states 'Get one application' with no mention of read-only behavior, authorization needs, or any side effects. This is insufficient for an agent to understand operational 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 has two sentences, but the second sentence is awkward and unclear: 'Recruiting applications for pipeline, stage, source, owner, and freshness analysis.' It could be more concise and structured.

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

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

Given the tool has 5 parameters, nested objects, and no output schema, the description is too brief. It does not explain return values or the purpose of parameters like include or query_json, leaving the agent 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?

With 80% schema coverage, the schema already describes most parameters. The description adds no additional meaning beyond what is 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 states 'Get one application' clearly identifying the verb and resource. However, it does not explicitly differentiate from sibling tools like list_applications, though the singular nature is implied.

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 list_applications or other recruiting tools. There are no exclusions or contextual hints.

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 bears full responsibility for behavioral disclosure. It merely says 'Get one candidate' with no mention of read-only nature, authentication requirements, rate limits, or any side effects. 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 short but includes an awkward second sentence that seems like a list of use cases rather than a coherent explanation. It could be more concise by simply saying 'Get one candidate.' The structure is acceptable but not optimal.

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, nested objects, and no output schema. The description is too minimal to cover what the returned candidate contains, or how to use parameters like 'include', 'query_json', and 'path_params'. Given the complexity, the description is incomplete.

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

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

The input schema has 80% description coverage, so the schema already documents most parameters. The description adds no additional meaning about parameters beyond what the schema provides. Baseline 3 is appropriate as the schema does the heavy lifting, but the description does not compensate for any gaps.

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

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

The tool description states 'Get one candidate' which clearly indicates the action and resource. It distinguishes from siblings like 'list_candidates' and 'get_person'. The second sentence 'Recruiting candidates for candidate lookup, source analysis, and application joins.' is somewhat redundant and doesn't add clarity, but does not detract significantly.

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 such as 'list_candidates' (for multiple candidates) or 'get_person' (if searching by person). The description does not provide context for selecting this tool over siblings.

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 responsibility. It fails to disclose whether the tool is read-only, what response format to expect, or any side effects. With zero behavioral context, the description is insufficient.

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

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

The description is a single, front-loaded sentence with no wasted words. However, it sacrifices clarity for brevity, so it does not achieve a perfect score.

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 no annotations, the description is too minimal. It does not explain what the tool returns, how to interpret the output, or any important behavioral details, leaving the agent under-informed.

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 zero parameters with 100% description coverage by default. The description adds meaning by indicating the tool shows coverage information, which is helpful. Baseline for zero parameters is 4.

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 it shows 'Personio Recruiting Ops Plane question, reporting, and action coverage,' which indicates a capability-checking tool but lacks specificity about what 'coverage' entails. It is not a tautology and is somewhat distinct from sibling tools that fetch specific resources.

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, nor any context about prerequisites or typical use cases. The agent receives no direction for tool selection.

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

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

With no annotations, the description should disclose behavioral traits like idempotency, error handling, or permissions, but it only states the basic retrieval function.

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. It could be slightly more structured but is 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 5 parameters, nested objects, and no output schema, the description is insufficient. It does not explain complex parameters like query_json or the 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 description coverage is 80%, so the baseline is 3. The description adds no additional parameter context, but the schema already covers most parameters adequately.

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

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

The description states it retrieves a single jobs_catalog_item and mentions its purpose for cross-checking. However, it does not differentiate it from sibling tools like get_recruiting_job or 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 description provides no guidance on when to use this tool or alternatives. It does not mention any 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?

No annotations provided, so description carries full burden. Only mentions 'for owner/function joins' as vague context. Does not disclose error behavior, read-only nature (implied), 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?

Very concise, one sentence with an additional clarifying fragment. No wasted words, but the phrase 'for owner/function joins' is slightly unclear and could be expanded 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?

Simple getter, but description does not address optional parameters or detail_profile enum that controls output. No output schema, so agent is left guessing about return format. Adequate for basic retrieval, but missing integration with schema 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 80%, so baseline is 3. The description adds no parameter-specific details beyond the schema. No mention of id, include, query_json, path_params, or detail_profile.

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?

Verb 'Get' and resource 'org_unit' are clear. The description also defines org units as 'departments and teams' with purpose 'for owner/function joins', distinguishing from sibling tools like list_org_units.

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 use for retrieving a single org unit, but lacks explicit when-to-use or when-not-to-use guidance compared to alternatives like list_org_units. No exclusions or prerequisites 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 provided, the description must disclose behavioral traits. It states 'Get one person' implying a read operation, but does not confirm idempotency, permissions, rate limits, or any side effects. The description lacks sufficient transparency for an unannotated tool.

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

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

The description is concise, only two sentences, and front-loads the core purpose. Every sentence is necessary and there is no filler.

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 there is no output schema, the description does not hint at the return value shape. The tool has 5 parameters, and while the schema covers most, the description is minimal. For a simple get tool, it is barely adequate but could be more 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 80% coverage, so most parameters are already documented. The description adds no additional parameter information beyond the schema. Since coverage is high, baseline is 3, but there is no added value from 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 the verb 'Get' and resource 'one person' from Personio, and provides context about resolving hiring-team person IDs. However, it does not explicitly differentiate from sibling tools like get_candidate or list_persons, though the mention of 'recruiting applications' provides some distinction.

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

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

The description implies use when needing a single person by ID, but provides no explicit guidance on when to use this tool versus alternatives such as get_candidate or list_persons. There is no mention of when not to use or prerequisites.

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

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

No annotations provided; description does not disclose behavioral traits such as read-only nature, error handling, authentication needs, or rate limits. For a tool without annotations, this is insufficient.

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

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

The description is very concise at two sentences with no redundant information. However, it sacrifices completeness for brevity, which slightly lowers the score.

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 details on return value, usage of detail_profile, or handling of ids. Without output schema, more context is needed to fully understand the tool's 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?

Schema description coverage is 80%, so the baseline is 3. The description adds no additional meaning beyond the schema; it does not explain any parameters or their use, but the schema itself provides decent 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 'Get one recruiting_category' indicating it retrieves a single category. It distinguishes from the sibling list_recruiting_categories by implying a singular retrieval, but does not explicitly differentiate.

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 vs alternatives like list_recruiting_categories. The phrase 'function-level slicing' is vague and does not clarify context or prerequisites.

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

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It does not state whether the operation is read-only, what happens if the ID is invalid, or any rate limits or auth requirements. The description adds minimal behavioral context beyond the name.

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

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

The description is very short and contains no redundant words. It is front-loaded with the core action. However, it is missing the second sentence's clarity, which reduces its effectiveness slightly.

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?

There is no output schema, so the description should explain what fields are returned. It only mentions vague 'opening inventory, category, department, and hiring-team joins' without explaining the response structure. The description leaves significant context gaps for a retrieval tool.

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

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

Schema description coverage is 80% (high), so the baseline is 3. The description adds no additional meaning to the parameters beyond what the schema already documents. For example, it does not explain the purpose of 'include', 'query_json', or 'path_params'.

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

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

The description clearly states the verb 'Get' and the resource 'recruiting_job', making the basic purpose obvious. However, the second sentence is somewhat confusing and fails to differentiate from the sibling 'list_recruiting_jobs' tool beyond the singular vs. plural nature, which is already implicit in the name.

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

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

The description provides no guidance on when to use this tool versus alternatives like list_recruiting_jobs, nor does it mention any prerequisites, contexts, or exclusions. The agent is left without any 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, so the description carries the behavioral disclosure burden. It mentions a limitation (recruiting-domain events not available) and implies a read operation, but does not disclose authentication needs, rate limits, or any side effects. The description is adequate but not thorough.

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 sentences long, front-loads the primary purpose, and contains no unnecessary words. 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 simple read tool with no output schema and good schema coverage, the description is nearly complete. It could mention the return type (e.g., a webhook object) but the purpose is clear. The limitation about recruiting-domain events is useful 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 high (80%), so the schema already documents parameters well. The description adds no additional meaning beyond what the schema provides, such as explaining usage of complex parameters like query_json or path_params. Baseline score of 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 'Get one webhook' and specifies the domain (Personio HRIS webhook configurations for delivery monitoring). It distinguishes from sibling tools like list_webhooks (for listing) and create/delete/update webhooks by explicitly being a retrieval operation.

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

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

The description does not explicitly state when to use this tool vs alternatives or when not to use it. It is implied by the name and the note about recruiting-domain events, but lacks explicit guidance on selection criteria or 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 fails to disclose any behavioral traits such as read-only nature, authentication requirements, or side effects. The bare 'Get one workplace' offers no insight beyond the operation name.

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

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

The description is very short and front-loaded, with two sentences that convey purpose and context. It is efficient, though the second sentence could be clearer.

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 no annotations, the description is insufficient for a tool with five parameters. It lacks information on return values, error handling, or usage 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 description coverage is high (80%), so the description does not need to add parameter details. However, it adds no extra meaning beyond the schema itself, remaining at the baseline.

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 workplace,' specifying a singular retrieval operation, and adds context with 'Workplaces for location/region slicing,' which distinguishes it from sibling tools like list_workplaces.

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 phrase 'Workplaces for location/region slicing' implies a use case but does not specify exclusions or 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?

With no annotations, the description carries full burden for behavioral disclosure, but it only mentions 'list' and analysis types, omitting critical traits like pagination, filtering, error conditions, or side effects. It does not indicate read-only or destructive nature.

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, front-loaded with the verb and resource. No unnecessary words or filler, achieving high efficiency.

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 output schema, numerous parameters (11), and no annotations, the description is far too brief. It does not explain return values, pagination, or how to use the complex parameters like query_json or path_params, making it 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 only 45%, so the description should compensate but provides minimal parameter insight. It hints at filtering by pipeline, stage, etc., but does not map to specific parameters or explain their usage, leaving many parameters undefined.

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 applications' and adds context about recruiting applications for specific analyses, making the purpose clear. However, it does not explicitly distinguish from sibling tools like list_candidates or list_recruiting_jobs, missing a chance for differentiation.

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

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

No guidance is provided on when to use this tool versus alternatives, nor are there any conditions or prerequisites mentioned. The description is purely declarative without 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?

With no annotations provided, the description carries the burden of behavioral disclosure. It states 'list' implying a read operation, and notes ordering (latest first), which is helpful. However, it does not explicitly confirm idempotence or non-destructive behavior, nor does it explain return format 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 extremely concise with two sentences, no redundant information. 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?

Given the complexity (9 parameters, no output schema, no annotations), the description is too brief. It omits how to specify the application, what the response contains, and how pagination or filtering works. A more complete description would guide the agent on 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 only 33%, and the description adds no parameter guidance. It does not explain which parameter(s) identify the application (likely path_params or query_json) or how to use the detail_profile or other filtering options. The agent must rely on the schema, which is insufficient for many 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' and the resource 'application_stage_transitions', specifies it's for one application, and notes ordering (latest first). It uniquely identifies this tool among siblings, no confusion.

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 the tool is for retrieving stage transition history of one application, but provides no explicit guidance on when to use it versus alternatives. It does not mention that the application must be specified via parameters, 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 provided; the description omits behavioral traits such as read-only nature, pagination details, rate limits, or authentication requirements. It only hints at the detail_profile parameter's effect.

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 short sentences with no redundancy, but the brevity sacrifices essential details. The verb 'list' is 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?

Despite having 9 parameters, nested objects, and no output schema, the description provides almost no contextual completeness. It fails to explain return structure, error handling, 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?

With only 33% schema description coverage, the description does not explain the majority of the 9 parameters (e.g., sort, include, query_json). Only detail_profile's options are partially described via its schema, but not in the description itself.

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 candidates' and adds context about use cases (candidate lookup, source analysis, application joins), distinguishing it from siblings like list_applications. However, it lacks specific scope 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 explicit guidance on when to use this tool vs alternatives. While it mentions use cases, it doesn't explain when to prefer this over get_candidate or list_applications, nor does it provide 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. The description does not disclose side effects, read-only nature, authorization needs, or rate limits. The verb 'list' implies idempotency but it's 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?

Very concise at two sentences, but the first sentence is nearly tautological ('List jobs_catalog'). The second adds context but could be more structured.

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

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

With 9 parameters, no output schema, and no behavioral context, the description is insufficient for an agent to use the tool correctly. Lacks explanation of paging, filtering, or response 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 description coverage is only 33%, and the description adds no parameter explanations. Of 9 parameters, only a few have schema descriptions; the tool description offers no help in understanding how to use them.

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 jobs_catalog' and specifies the purpose: 'for cross-checking recruiting job metadata'. It distinguishes from sibling tools like list_recruiting_jobs, but could be more precise about what exactly is listed.

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., list_recruiting_jobs, get_jobs_catalog_item). The phrase 'for cross-checking' hints at use case but is insufficient.

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 must disclose behavioral traits. It does not mention pagination, rate limits, authentication requirements, or what happens with empty results. The phrase 'for owner/function joins' is vague and insufficient.

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

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

The description is concise, with two short sentences front-loading the purpose. However, it sacrifices necessary detail for brevity, which lowers the score from perfect.

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 severely incomplete. It does not explain pagination, filtering, sorting, response format, or how to use the included parameters 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 33% (only 3 of 9 parameters have descriptions). The tool's description does not add any parameter semantics or clarify undocumented parameters like page, sort, limit, cursor, include, or per_page. It fails 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 clearly states the tool lists org units and defines them as departments and teams for owner/function joins. It distinguishes from sibling tools because no other sibling lists org units, but it could be more specific about the 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 explicit guidance on when to use this tool versus alternatives (e.g., get_org_unit for a single unit). The description provides implicit context but lacks when-not-to-use or 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 are provided, so the description carries the full burden of disclosing behavioral traits. It only states 'List persons' without mentioning pagination, sorting, filtering, side effects, or whether the operation is read-only. The tool has nine parameters including pagination controls, but these are not described.

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, making it concise and front-loaded. However, it sacrifices necessary detail for brevity, omitting important information about parameters and behavior. It is appropriately short but incomplete.

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, many siblings), the description is insufficient. It fails to explain pagination, filtering, or response format, and does not differentiate clearly from other list tools. The narrow use case is helpful but does not cover the tool's full capabilities.

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% (three out of nine parameters have descriptions). The tool's description adds no parameter information at all, failing to compensate for the low coverage. Key parameters like page, sort, limit, cursor, and per_page remain undocumented in both the schema and 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 lists 'persons' from Personio, and provides a specific use case ('resolving hiring-team person IDs returned by recruiting applications'). This distinguishes it from sibling tools like list_applications or list_candidates, though it does not explicitly differentiate from get_person.

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 gives a specific context for use (resolving person IDs from recruiting applications), implying when to use the tool. However, it does not specify when not to use it or provide alternatives among the many sibling list or get tools.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It only states 'list' with no details on pagination behavior, rate limits, or what happens if no categories exist, and does not mention whether data is read-only or has 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?

Two short sentences with no wasted words. The purpose is front-loaded, making it easy for an agent to quickly understand the tool's function.

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

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

Given 9 parameters, no output schema, and no annotations, the description is severely incomplete. It lacks details on pagination, filtering options, returned fields, and operational behavior, making it insufficient for an agent to invoke 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-specific information beyond the schema, failing to compensate for the low coverage. Parameters like page, sort, limit, and cursor are left unexplained.

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 recruiting_categories' with a specific verb and resource, and adds context 'Recruiting job categories for function-level slicing', which distinguishes it from sibling tools like list_recruiting_jobs or get_recruiting_category.

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 context on prerequisites or exclusions, and no mention of 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 carries the full burden of behavioral disclosure. It only states 'List recruiting_jobs' without explaining pagination, sorting, filtering, or other behavioral traits. The schema parameters imply features like cursor-based pagination and field selection, but the description does not address them.

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 ineffective. The first sentence is a tautology (restating the tool name). The second sentence is grammatically awkward and unclear. It is not front-loaded with key information; instead it wastes space.

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 many sibling tools, the description is severely incomplete. It does not explain pagination, filtering, result shape, or how detail_profile affects output. This is completely inadequate 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 description coverage is only 33%, meaning most parameters lack descriptions. The tool description adds no information about parameters such as page, sort, limit, cursor, include, per_page, query_json, or path_params. It fails to compensate for the low schema coverage.

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

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

The description clearly states the verb 'List' and the resource 'recruiting_jobs'. However, it does not distinguish this tool from sibling list tools like list_candidates or list_applications, and the second sentence about 'opening inventory, category, department, and hiring-team joins' is 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 is provided on when to use this tool versus alternatives such as get_recruiting_job, list_candidates, or other list endpoints. The description does not specify criteria for selecting 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?

No annotations are provided, so the description must fully explain behavior. It mentions the 30-day limit and single-webhook scope but omits important traits like pagination behavior (implied by cursor/limit params), whether it is read-only, or any side effects. The word 'List' suggests read-only but is 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?

The description is short (one sentence) and front-loaded, which is efficient. However, it lacks structure and omits critical information, making it under-specified rather than appropriately 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 9 parameters, no output schema, and no annotations, the description is insufficient. It does not explain return values, how to specify the webhook ID, or how pagination works. The context signals indicate high complexity that is not addressed.

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?

Only 33% of parameters have schema-level descriptions (query_json, detail_profile, path_params). The tool description adds no explanation for any of the 9 parameters, leaving their purpose and usage unclear. For example, 'cursor' and 'include' are not mentioned.

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') and the resource ('webhook_activity'), and specifies the time range ('last 30 days') and scope ('for one webhook'). However, it does not differentiate from sibling tools like list_webhook_events, which may have overlapping functionality.

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 does not mention prerequisites, exclusions, or typical use cases. Sibling tools exist but are not referenced.

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 does not explicitly state that this is a read-only operation, nor does it disclose any side effects, rate limits, or authentication needs. The 30-day constraint is noted but insufficient.

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

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

The description is short and front-loaded, but it omits critical information, making it under-specified rather than concise. It could be shorter if it added necessary 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?

Given the complexity (9 parameters, no output schema, low coverage), the description is incomplete. It fails to explain how to specify the webhook, handle pagination, or interpret results.

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

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

Schema description coverage is only 33%, and the description fails to clarify which parameter selects the 'one webhook' it mentions. The schema lacks a webhook_id parameter, leaving ambiguity. The description adds little meaning beyond what the schema 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?

The description clearly states the verb 'list', the resource 'webhook_events', and the scope: 'HRIS webhook event deliveries from the last 30 days for one webhook.' This distinguishes it from siblings like 'list_webhooks' 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?

The description implies this tool is for listing events from a specific webhook within the last 30 days, but it does not explicitly state when to use it versus alternatives like 'list_webhook_activity' or mention prerequisites or exclusions.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic action ('List webhooks') and a domain limitation, but omits critical details such as authentication requirements, rate limits, pagination behavior, or what happens when no webhooks exist. The tool is a read operation, but more context is needed.

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 sentences long and front-loaded with the core purpose. It contains no redundant information and every phrase adds value. This is highly concise and well-structured.

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

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

Despite having no output schema and 9 parameters, the description is very brief. It does not explain return values, filtering, sorting, pagination, or any other contextual details. The tool is relatively complex (pagination, multiple parameters) but the description provides minimal completeness, making it harder for an agent to use 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?

The input schema has 9 parameters with only 33% having descriptions (query_json, path_params, detail_profile). The tool description does not add any additional meaning for the other 6 parameters (page, sort, limit, cursor, include, per_page). Given the low schema coverage, the description should compensate but does not, leaving agents uncertain about parameter usage.

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 webhooks' and specifies the domain as 'Personio HRIS webhook configurations for delivery monitoring.' It also explicitly notes that 'Recruiting-domain events are not available,' which helps distinguish it from other tools. The verb+resource combination is specific and unambiguous.

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 contextual clues about when to use the tool (for delivery monitoring of HRIS webhooks) and a limitation (recruiting events not available). However, it does not explicitly mention when not to use this tool versus alternatives like list_webhook_activity or redeliver_webhook_events, which would strengthen guidance.

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 only states 'List workplaces' and gives a brief use context, but fails to mention important details like pagination behavior, 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 concise with two short sentences, no redundancy, and front-loaded information. However, given the tool's complexity (9 parameters), it may be overly 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?

For a tool with 9 parameters, no output schema, and no annotations, the description is insufficient. It lacks parameter explanations, return value description, and usage examples, making it incomplete for effective agent invocation.

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

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

Schema description coverage is low (33%), yet the description adds no information about the 9 parameters. It does not explain the meaning of common pagination parameters (page, limit, cursor) or specialized ones like detail_profile and query_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 'List workplaces' as a verb+resource combination. The added phrase 'Workplaces for location/region slicing' gives context but does not explicitly differentiate from sibling list tools like list_org_units or 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 implies usage for location/region slicing but provides no explicit guidance on when to use this tool versus alternatives such as get_workplace or other list_* tools. No exclusions or when-not-to-use 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?

The description lacks disclosure of behavioral traits such as side effects, required permissions, or rate limits. Annotations are absent, so the description carries the full burden but fails to explain the impact of the ping (e.g., whether it sends a test event or merely checks connectivity). The generic parameter names (confirm, dry_run, body_json) also suggest hidden complexity not addressed.

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 at one sentence, but it is too minimal. It is front-loaded with the key verb and resource, but every word is earned. A slightly longer description could improve clarity without harming 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 complexity of the input schema (6 parameters, all optional but including confirm/dry_run and HTTP-like fields) and no output schema, the description is severely incomplete. It does not explain what the tool returns, how parameters like body_json or path_params relate to a ping, or the expected behavior. The description alone is insufficient 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 coverage is 100%, so the baseline is 3. However, the parameter descriptions in the schema are generic (e.g., 'JSON request body for documented write operations') and not tailored to this tool's specific use. The tool description adds no parameter semantics beyond the schema, and the generic descriptions may mislead an agent about how to use confirm/dry_run with a ping.

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 'Send a Personio webhook ping event' clearly states the action (send) and the resource (webhook ping event). It distinguishes the tool from sibling tools like create_webhook or delete_webhook. However, it does not elaborate on what a 'ping' entails, leaving some ambiguity about the 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?

No usage guidance is provided. The description does not indicate when to use ping_webhook versus alternatives like redeliver_webhook_events or test endpoints. There are no when-to-use or when-not-to-use instructions.

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

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It only says 'Redeliver selected webhook events', implying mutation, but fails to specify whether this creates duplicate events, requires specific permissions, or has side effects like rate limiting.

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 short (4 words) and lacks necessary detail. While concise, it is under-specified for a tool with 6 parameters and no annotations, requiring the agent to rely on generic parameter descriptions without context.

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 is severely incomplete. It does not explain how to select events, what the confirm/dry_run parameters do in context, or what the return value or success criteria are. With 6 generic parameters and no output schema, the agent has insufficient information to use the tool effectively.

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

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

Schema coverage is 100%, with all six parameters having descriptions. The tool description adds no additional meaning beyond what the schema already provides, so a baseline score of 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 verb 'Redeliver' and the object 'selected webhook events', making the primary action identifiable. It distinguishes from siblings like list_webhook_events and ping_webhook, which are about listing or testing rather than re-sending.

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?

There is no guidance on when to use this tool versus alternatives like ping_webhook or create_webhook. The description does not mention prerequisites, such as needing a webhook id or event selection, nor does it advise 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?

The description does not disclose behavioral traits such as the need for confirmation (despite the confirm parameter) or whether the update is live or previewable. Without annotations, the description carries the full burden but provides no extra context.

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

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

The description is a single sentence, which is concise but not structured. It lacks front-loading of key information and does not organize content for quick scanning.

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 six parameters (including confirm/dry_run) and the absence of an output schema, the description should explain what the update does and what is returned. The terse 'Update a Personio webhook' is insufficient for a mutation tool.

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

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

Schema description coverage is 100%, with each parameter having a description. The tool description adds no additional meaning beyond what the schema already provides. Baseline score of 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 the verb 'update' and resource 'Personio webhook', but lacks specificity about what aspects are updatable. It does not differentiate from siblings like create_webhook or delete_webhook, which also target webhooks.

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 creating or deleting webhooks. No prerequisites or context are provided, leaving the agent to infer usage from the tool name alone.

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

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

No annotations provided. The description does not disclose behavioral traits such as mutation side effects, permission requirements, or the effect of confirm/dry_run parameters. Return value is not described.

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 the action. 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 7 parameters including nested objects and a confirm/dry_run pattern, the description lacks context on workflow, prerequisites, and how the document attaches to a new application. Incomplete for a tool of this complexity.

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

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

Schema description coverage is 100%, so the schema carries the load. The description adds the hint about providing base64 or URL, which is helpful but not extensive.

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 'Upload', the resource (a document to Personio attached to a recruiting application), and gives an example (CV). It distinguishes from sibling tools as no other tool directly uploads documents.

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 guidance on how to provide the file (base64 or URL). It implicitly indicates when to use (for uploading documents to recruiting applications), but does not explicitly state when not to use or mention alternatives.

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