TalentLyft Ops Control Plane

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

With no annotations, the description must disclose behavioral traits. It only states 'use any endpoint' without mentioning side effects, error handling, rate limits, or authorization details beyond the saved connection.

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 immediately conveys the tool's purpose with no wasted words.

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

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

For a generic proxy tool with 6 parameters and no output schema, the description is insufficient. It lacks details on path construction, authentication, error handling, and return value 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 coverage is high (83%), so the description doesn't need to add much. However, it does not elaborate on how parameters relate to endpoints, adding minimal value beyond the schema.

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

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

The description clearly states the tool's purpose: to call any documented TalentLyft endpoint using the buyer's connection. This distinguishes it from sibling tools that target 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?

While it doesn't explicitly say when not to use this tool, the context implies it's for endpoints without a dedicated sibling tool. The description provides clear usage context but no exclusions.

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

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It only states 'Create', which implies mutation, but does not mention effects, permissions, or error conditions.

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, but it lacks any structure or prioritization of key information. It does not front-load important usage 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 tool has 5 parameters (including a complex 'body_json' object) and no output schema, the description is far too minimal. It fails to explain the payload structure, required fields, or what the response indicates.

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. The description adds no additional meaning to the parameters; it relies entirely on the schema descriptions for each parameter.

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

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

The description clearly states the action ('Create') and the resource ('a TalentLyft candidate'), which identifies the tool's purpose. However, it does not provide any additional context to differentiate it from sibling tools like 'create_job' or 'update_candidate'.

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 compared to alternatives (e.g., 'update_candidate' for existing candidates) or any prerequisites for creating a candidate.

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 the full burden of behavioral disclosure. It fails to mention that this is a write/mutation operation, whether it is idempotent, what side effects occur (e.g., creating a new resource), or any authentication or rate-limiting considerations.

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, highly concise with no wasted words. However, for a creation tool with 5 parameters and nested objects, the brevity may sacrifice necessary detail, though conciseness itself is well-executed.

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 (5 parameters, nested objects, no output schema) and absence of annotations, the description is severely lacking. It does not explain which parameters are required for successful creation, the expected response, or how the job creation integrates with the broader system.

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

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

Schema description coverage is 100%, so all parameters are documented in the schema itself. The description adds no additional parameter-level context beyond what the schema provides, meeting the baseline expectation of 3 with no improvement.

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

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

The description clearly states the verb 'Create' and the resource 'TalentLyft job', directly identifying the tool's action. It is distinct from siblings like 'create_job_requisition' and 'update_job', though a brief clarification of what constitutes a 'TalentLyft job' could improve 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 like 'create_job_requisition' or 'update_job'. There are no prerequisites, caveats, or context for invocation, leaving the agent to guess the appropriate scenario.

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, but it only states the action. It does not mention side effects, required permissions, or what the dry_run parameter implies. The description is insufficient for a mutation tool.

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

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

The description is extremely concise (5 words), but lacks necessary detail. While brevity is valued, it sacrifices informativeness. A slightly longer description with context would be better.

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

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

Given no annotations, no output schema, and 5 parameters with nested objects, the one-sentence description is completely inadequate. It fails to explain what a job requisition is, how it differs from a job, or what the body_json should contain. The agent lacks crucial 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 100% with descriptive parameter texts, so the description adds no extra parameter meaning. The baseline score of 3 is appropriate as the schema already handles parameter semantics.

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

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

The description clearly states the verb ('Create') and the resource ('TalentLyft job requisition'), making the action unambiguous. However, it does not distinguish this from the sibling 'create_job', which could be confused.

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 'create_job' or 'api_request'. No context about prerequisites or conditions is given.

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 only states 'Get one candidate' and mentions analysis types but does not disclose read-only nature, authentication needs, rate limits, or what data is returned. The presence of complex parameters like query_json and path_params is unaddressed.

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 one clear sentence and a short fragment. It is front-loaded with the core purpose. However, the fragment about analyses feels tacked on and could be integrated more smoothly.

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 (6 parameters, nested objects, no output schema, no annotations), the description is inadequate. It does not explain return values, behavior, or when to use specific parameters like reason or detail_profile.

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 83%, so baseline is 3. The description adds no information about the 6 parameters (id, reason, include, query_json, path_params, detail_profile) beyond what is in the schema. It does not clarify the usage of complex 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 'Get one candidate' (verb+resource) and adds context about use cases (stale-candidate, etc.). This distinguishes it from siblings like list_candidates which retrieve multiple 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 implies usage for retrieving a single candidate but provides no explicit guidance on when to use alternatives like list_candidates or get_candidate_application. No when-not 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 burden. It mentions the tool 'gets' an application, which is typical for a read operation, but does not disclose behavioral traits like default field set, error handling, or side effects. Adequate but minimal.

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, front-loading the core action. No wasted words; every part contributes to understanding.

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?

No output schema exists; the description hints at return fields (stage, job, disposition) but is not explicit. For a simple get operation with 6 parameters (some optional), it is minimally sufficient but lacks detail on optional parameters and return 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 83%, so the schema already explains most parameters. The description adds only a high-level note about analysis purpose but does not clarify specific parameters like 'reason' or 'include'. Baseline 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 it retrieves a single candidate_application and its purpose for analysis of stage, job, and disposition. It effectively distinguishes from sibling tools like list_candidate_applications (list) and update_candidate_application (update).

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 retrieving a single application but does not provide explicit guidance on when to use this tool versus alternatives (e.g., list for multiple, update for modifications). No exclusions or alternative suggestions are given.

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 does not disclose any behavioral traits such as side effects, authentication needs, or rate limits. It only mentions a vague 'coverage'.

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

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

Single sentence, no redundancy. However, it is slightly under-specified; conciseness is good but at the cost of 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?

Given no output schema and zero parameters, the description should explain what the output represents. 'Coverage' is ambiguous; the agent cannot infer the return structure or content.

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%. The description does not need to explain parameters, but it adds nothing beyond the schema. Baseline 4 is appropriate.

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

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

Description states 'Show ... coverage' which indicates a verb and resource, but 'question, reporting, and action coverage' is vague and lacks specificity. It does not clearly differentiate from sibling tools that also retrieve information.

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 other get/list tools. The description does not indicate scenarios 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, and the description does not disclose behavioral traits such as whether the tool is read-only, required permissions, rate limits, or error handling. The only implied behavior is that it retrieves a single department, which is minimal.

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, consisting of two sentences that front-load the core purpose. Every word is meaningful and no extraneous content is present.

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 6 parameters and no output schema, the description fails to explain how to use parameters like 'query_json' or 'path_params', nor does it describe the response format. For a tool that retrieves a single entity, more context (e.g., what fields are returned, default behavior) is needed to be fully complete.

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

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

Schema description coverage is 83% (high), so the schema already documents most parameters. The description does not add any additional meaning beyond the schema. It neither clarifies nor detracts from parameter semantics, earning the baseline score.

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 department' which specifies the verb and resource. It also provides context about departments being for 'role/function slicing where enabled in the tenant', and distinguishes from sibling tool 'list_departments' by indicating it retrieves a single 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 does not provide any guidance on when to use this tool versus alternatives. It does not mention when not to use it or suggest other tools like list_departments for retrieving multiple departments.

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 only states the tool 'gets' an event, implying a read operation without side effects, but fails to mention any important behaviors such as idempotency, rate limits, or authentication requirements. The mention of 'operational history and audit-style joins' adds some context but 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, which is good for a simple get tool. However, it could be slightly more informative without becoming verbose. It is front-loaded with the core action, making it easy to scan.

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 and the tool's complexity (6 parameters, nested objects), the description is incomplete. It does not explain what the returned event looks like, whether pagination is involved, or how the 'detail_profile' parameter affects output. The description leaves significant gaps for an agent to understand the tool's full 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 high (83%), so the schema already documents parameters well. The description adds no new parameter-specific information beyond hinting at the tool's use case. Baseline 3 is appropriate as the description is neither helpful nor harmful for parameter understanding.

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

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

The description clearly states it gets one event, specifically 'recruiting events for operational history and audit-style joins.' This distinct purpose differentiates it from sibling tools like list_events, which lists multiple events, and other get tools for different entities.

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

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

The description provides no guidance on when to use this tool versus alternatives like list_events or other get tools. It does not specify prerequisites, typical use cases, or when not to use it, leaving the agent to infer context 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 are provided, so the description carries full burden. It only says 'Get one form' without disclosing any behavioral traits such as authentication needs, error handling, rate limits, or side effects. The description is insufficient for understanding 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 very short (one sentence), which is concise but not structured effectively. It lacks a clear breakdown of key information and does not front-load the most 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?

Given the tool has 6 parameters including nested objects and no output schema, the description is far too brief. It does not explain return values, parameter usage, or how to effectively invoke the tool. 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?

Schema coverage is 83%, so the schema already documents most parameters. The description adds no additional meaning to the parameters beyond what the schema provides. Baseline 3 is appropriate.

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

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

The description states 'Get one form. Forms and application structure metadata.' It clearly indicates the tool retrieves a single form, distinguishing it from sibling list_forms. However, the phrase 'application structure metadata' is ambiguous and could be clarified.

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_forms or other get tools. No when-to-use or when-not-to-use information is given.

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 the full burden. It only states 'Get one job' with no disclosure of read-only behavior, authentication needs, rate limits, or any side effects. This is insufficient for an agent to understand the tool's operational context.

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

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

The description is short (two sentences) but includes a vague second sentence that adds little value. It could be more concise by removing the second sentence or replacing it with actionable 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 complexity of 6 parameters (including nested objects) and the absence of an output schema, the description fails to explain what a job object contains or how the tool behaves. Important details about the detail_profile parameter and response format are missing.

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 83%, meaning most parameters have basic descriptions in the schema. The description adds no additional meaning beyond the schema, such as explaining how parameters like detail_profile affect the output or how to use query_json effectively.

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 starts with 'Get one job', which clearly states the verb and resource. However, the second sentence about use cases is vague and doesn't effectively differentiate from sibling tools like list_jobs, 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?

There is no guidance on when to use this tool versus alternatives such as list_jobs or get_job_requisition. No context about preferred scenarios or exclusions is provided.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. However, it only says 'Get one job_board_post' without mentioning whether the operation is read-only, what authentication is required, rate limits, or response format. This is insufficient for safe and correct invocation.

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 redundant information. It is front-loaded with the core action and provides supplementary 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 tool has 6 parameters, nested objects, and no output schema, the description falls short. It omits details on return values, behavior for different parameter combinations, and error handling. The minimal description does not compensate for these gaps.

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

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

With schema description coverage at 83%, the input schema already describes most parameters adequately. The description adds no parameter-specific information, which is acceptable given the high coverage. A score of 3 is baseline for such cases.

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

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

The description clearly states the verb 'Get' and the resource 'job_board_post', and provides context about what job-board posts are used for ('posting visibility and source-quality context'). This distinguishes it from sibling tools like list_job_board_posts, which retrieves multiple posts.

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 versus alternatives (e.g., list_job_board_posts). It only implies usage for retrieving a single post, but offers no guidance on when not to use it or what to do instead.

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 'Get one job_requisition' and the context, without describing side effects, authentication requirements, rate limits, or limitations. Important traits like the reason parameter requirement or what happens with optional parameters are not mentioned.

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

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

The description is very concise, consisting of two short sentences with no unnecessary words. It conveys the essential purpose and context efficiently, making it easy to parse.

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

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

Given the tool has 6 parameters with nested objects and no output schema, the description is too minimal. It does not explain the usage of parameters like query_json or path_params, nor does it describe the return format or any constraints. The agent would need to rely solely on the schema, 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?

The input schema has 83% description coverage, so the baseline is 3. The description adds no parameter-specific information beyond what is already in the schema. It does not elaborate on any parameters, so it meets but does not exceed 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 job_requisition', specifying the verb and resource. It adds context with 'for headcount and approval-flow investigations', distinguishing it from siblings like list_job_requisitions and other get_* tools. This meets the criteria for a specific verb+resource and differentiation.

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

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

The description provides clear context by indicating the tool is used for headcount and approval-flow investigations, implying when it should be used. However, it does not explicitly mention when not to use it or list alternatives like list_job_requisitions, so it falls short of a 5.

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 traits are disclosed beyond the basic action. With no annotations, the description fails to indicate if the operation is read-only, has side effects, or requires specific permissions. This is a significant gap.

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

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

The description is very brief (2 sentences), but conciseness is not a virtue here as it lacks important detail. It is front-loaded with the purpose but does not earn its space with substantive content.

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

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

Given the tool has 6 parameters including nested objects and no output schema, the description is inadequate. It does not explain the structure of the returned member, parameter usage beyond schema, or any constraints.

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 (83%), so the schema already documents most parameters. The description adds no additional meaning to the parameters, but the baseline of 3 is appropriate since schema coverage is sufficient.

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 member, specifying the resource ('member') and action ('get'). It distinguishes from sibling 'list_members' by indicating it gets one member.

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 mention when to use this tool versus alternatives like get_candidate or list_members, nor any prerequisites or context for invalidity.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Get one pipeline' without explaining any behavioral traits like required permissions, parameter effects (e.g., detail_profile, reason), error handling, or return format. The high schema coverage does not compensate for the lack of behavioral context 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 very concise at two sentences and 9 words, with no redundant information. It is front-loaded and efficient, though it could include more context 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 (6 parameters, 1 required, nested objects, no output schema), the description is too minimal. It fails to explain the entity or response structure, how to use parameters like detail_profile, or the difference between operational and full profiles. The high schema coverage partially mitigates this, but the description should provide 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?

The schema description coverage is high (83%), so the baseline is 3. The description adds no additional meaning beyond the parameter descriptions already in the schema, which is adequate.

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 pipeline' with a specific verb and resource, distinguishing it from the sibling 'list_pipelines'. It also adds context about pipelines being for 'stage-model and conversion analysis', clarifying 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?

The description implies usage when a single pipeline is needed, contrasting with list_pipelines for multiple pipelines, but does not explicitly state when to use or not use this tool, nor mention any prerequisites or alternatives beyond the sibling.

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 'Get' which suggests a read operation. No details on idempotency, authorization, rate limits, error states, or side effects are disclosed.

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 with two sentences. The first sentence is front-loaded and clear. The second sentence adds marginal context. Could be slightly more concise but overall 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 6 parameters and no output schema or annotations, the description leaves out return value format, error handling, and other critical context. It is insufficient for an AI agent 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 83%, so the schema already describes the parameters. The description adds no extra meaning about parameters, so it meets the baseline but does not enhance understanding.

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

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

The description clearly states 'Get one rejection_reason' which identifies the verb and resource. However, it does not explicitly differentiate from sibling tool 'list_rejection_reasons', though the singular 'one' implies a specific instance retrieval.

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?

Usage is implied: use when you need a specific rejection reason by ID. No explicit when-not or alternative suggestions are given, but the naming and singular form provide some 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 fails to mention pagination, filtering, authentication, or side effects. As a read operation, it lacks a statement of non-destructiveness. The description adds minimal behavioral context beyond the tool name.

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

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

Two brief sentences, front-loaded with the action, no redundant words. The title is not provided, but the description is efficiently structured for quick understanding.

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 10 parameters, no output schema, and no annotations. The description only provides a high-level purpose. It omits details on response structure, pagination, filtering, and error handling. Given the complexity, the description is far from complete.

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

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

Schema description coverage is 40%, but the description does not mention any parameters. It adds no meaning beyond the schema. For the 60% of parameters lacking schema descriptions, the description provides no 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?

The description starts with 'List candidate_activities', clearly stating the verb and resource. The second sentence explains the purpose ('for follow-up, stale-work, and funnel-movement evidence'), which adds context and distinguishes it from sibling list tools that list other entities.

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

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

No guidance on when to use this tool versus alternatives. With many sibling list tools (list_candidates, list_events, etc.), the description does not specify scenarios or differentiate 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 exist, and the description does not mention behavioral traits like read-only nature, pagination, rate limits, or authentication needs. The name implies a read operation but lacks explicit confirmation.

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) and front-loaded with the action, but it sacrifices completeness for brevity. It is not well-structured and lacks important details.

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

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

The tool has 10 parameters, no output schema, and 40% schema coverage. The description fails to explain the tool's purpose (e.g., whether it lists all applications or per candidate), pagination, filtering, or the use of complex parameters like query_json and path_params. It is severely incomplete.

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

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

The description does not explain any of the 10 parameters. Although the schema covers 40% with descriptions for some parameters (reason, query_json, path_params, detail_profile), the description adds no value, which is critical given 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 states 'List candidate_applications' which is a clear verb+resource, but the additional phrase 'for stage, job, and disposition analysis' is vague and does not specify the scope (e.g., which candidate). It does not distinguish from sibling tools like list_candidates or get_candidate_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 is provided on when to use this tool versus alternatives such as get_candidate_application or list_candidate_activities. No prerequisites, exclusions, or context are mentioned.

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

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

With no annotations, the description must communicate behavioral traits. It fails to mention that the tool supports pagination, sorting, filtering, or the different detail profiles. The tool's behavior is almost entirely opaque.

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 but fails to pack essential information. It is not front-loaded with key details; instead, it wastes space on vague analysis categories. It is underspecified rather than 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 10 parameters, nested objects, no output schema, and high tool complexity, the description is wholly insufficient. It ignores pagination, filtering, output structure, and optional versus required parameters, leaving the agent without critical invocation 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 description coverage is 40%, but the description adds no parameter meaning. For the 60% of parameters lacking schema descriptions, the description offers no clarification, leaving the agent to guess semantics for parameters like 'reason', 'include', 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 states 'List candidates' which is a clear verb and resource, but the additional phrase 'Candidates for stale-candidate, source-quality, owner, and follow-up analysis' is vague and doesn't distinctly differentiate from sibling tools like list_candidate_activities or list_candidate_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 context is provided about when to use this tool versus alternatives, no prerequisites, and no exclusions. The description lacks any guidance on appropriate usage scenarios.

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

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

No annotations are provided, so the description carries full responsibility. It does not disclose pagination behavior, authorization needs, rate limits, or side effects. The schema hints at pagination and filtering, but the description adds no behavioral context beyond 'lists departments.'

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 (two sentences) and front-loads the purpose, which is good for conciseness. However, it sacrifices necessary detail and could benefit from expanded structure, such as mentioning core behavior or common use cases.

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 (10 parameters, nested objects, no output schema), the description is vastly incomplete. It fails to explain return values, pagination, filtering options, or parameter dependencies like 'reason' being required when detail_profile=full.

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 40%, and the description adds no parameter information. Parameters like page, cursor, and detail_profile are left unexplained by the description, relying entirely on the schema. The description should compensate for low schema coverage but does not.

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 departments' as the action and resource. It adds context that departments are used for role/function slicing and availability depends on tenant configuration, distinguishing it from get_department which retrieves a single record. However, it could be more explicit about listing all departments or supporting filtering.

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_department or other list_* tools. There is no mention of prerequisites, limitations, or comparison with sibling tools.

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

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

No annotations are provided, so the description should disclose behavioral traits like read-only, side effects, or rate limits. It only states 'List events' and vague purposes, without additional behavioral context.

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

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

The description is short at two sentences, but the second sentence is vague and adds little value. It is front-loaded appropriately but could be more informative 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?

With 10 parameters, no output schema, and no parameter explanations in the description, the context is incomplete. The description does not cover pagination, filtering, or expected output, leaving significant gaps for the agent.

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

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

Schema description coverage is 40%, meaning many parameters lack descriptions in the schema. The tool description does not explain any parameters or add meaning beyond what is in the schema, failing 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?

Describes the tool as listing events specifically for recruiting, with mention of operational history and audit-style joins. This provides a clear verb and resource, though it does not fully differentiate from sibling tools like list_candidate_activities or get_event.

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 get_event or other list tools. The description does not mention prerequisites, context, 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?

With no annotations, the description carries the full burden but fails to disclose behavioral traits. It does not mention that the operation is read-only, nor does it describe pagination, sorting, or any side effects. The description is minimal and provides little beyond the tool name.

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

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

The description is extremely brief (two short sentences), which might be considered concise, but it omits essential information. The first sentence is front-loaded with the action, but the lack of detail makes 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's complexity (10 parameters, nested objects, no output schema), the description is wholly inadequate. It does not explain pagination, filtering, return structure, or the purpose of parameters like 'query_json' and 'detail_profile'. The description leaves the agent without enough 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 description coverage is only 40%, leaving many parameters undocumented. The description adds no context for any parameter, such as 'page', 'sort', 'detail_profile', or 'reason'. It fails to compensate for the gaps in the schema.

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

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

The description clearly states the action 'List forms' with the resource 'forms'. It distinguishes from the sibling tool 'get_form' which retrieves a single form. However, it lacks specificity about the scope or type of forms, and the addition 'Forms and application structure metadata' 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 like 'get_form' or other list tools. There is no mention of prerequisites, filtering, 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 exist, so description should disclose behaviors like pagination, filtering, or required fields. It only repeats the name and gives a vague purpose, omitting all behavioral details.

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

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

Two sentences, short and front-loaded, but the second sentence adds little value and is somewhat redundant. Could be more 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 10 parameters, nested objects, no output schema, and no annotations, the description is severely incomplete. It does not cover pagination, filtering, profiles, or return 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?

With only 40% schema description coverage, the description adds no parameter meaning beyond the schema. It does not explain critical parameters like page, cursor, reason, 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?

Description clearly states 'List job_board_posts' as the verb+resource, distinguishing it from the sibling 'get_job_board_post'. The added phrase about visibility and source-quality context adds some clarity but 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 on when to use this tool versus alternatives like list_jobs or other list tools. No exclusions, prerequisites, or use-case 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 provided; description lacks disclosure of pagination behavior, authentication needs, rate limits, or what the data represents beyond a list.

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, focused and front-loaded; could be more informative but not wasteful.

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?

No output schema, no annotations, 10 parameters with incomplete schema descriptions; the description fails to explain paging, profiles, or operational 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 coverage is low (40%), but the description adds no explanation for parameters like cursor, sort, or page; does not help agent understand 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 job_requisitions' and adds context 'for headcount and approval-flow investigations', distinguishing it from other list tools like list_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?

Implied usage for headcount and approval-flow, but no explicit guidance on when to use this tool over alternatives like list_jobs.

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 'list', implying read-only, but does not mention pagination, output format, side effects, or any constraints. This is insufficient for a tool with 10 parameters.

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

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

The description is extremely concise with two sentences, no redundancy, and essential information 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 complexity of 10 parameters, nested objects, and no output schema, the description is far too brief. It lacks essential details like pagination, filtering, and return value explanation.

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 explain any parameter semantics. Schema description coverage is only 40%, and the description fails to compensate for the undocumented 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') and the resource ('job_requisition_status_logs'), and provides context about the domain ('approval and opening-lifecycle bottlenecks'). This distinguishes it from sibling tools like list_job_requisitions or list_job_status_changes.

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

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

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical use cases, or when to prefer other list 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 exist, so the description must disclose behavioral traits. It fails to mention pagination, filtering, authentication requirements, or any side effects. The description is too vague to inform the agent about important 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?

While very short (two sentences), it is underspecified rather than concise. The description should provide more details in a compact form, but it lacks critical information about parameters and usage, making it insufficient.

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 10 parameters, nested objects, and many sibling list tools, the description is woefully incomplete. It does not address the rich schema, common use cases, or how to effectively use the tool. The agent would struggle to invoke it correctly.

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

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

Schema description coverage is only 40%, meaning many parameters lack documentation. The description does not compensate by explaining any parameters, their purpose, or usage. For example, 'cursor', 'reason', 'include', 'query_json', etc., 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 'List jobs' as a specific verb and resource. The added phrase 'Jobs for open-role inventory, hiring-team analysis, and stage joins' provides some use-case context, but does not differentiate from sibling list tools like list_job_requisitions or list_job_stages, which could also serve those purposes.

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

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

No guidance is provided on when to use this tool versus alternatives. With multiple list tools for jobs and related entities, explicit usage instructions are essential, but the description offers none.

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 should disclose behavioral traits such as read-only nature, pagination behavior, or auth requirements. It does not mention any of these, only restating the tool's purpose.

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

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

The description is short but wasteful: the first sentence is a tautology of the tool name. The second sentence adds jargon ('stage-conversion', 'stale-pipeline') that may not be clear. Could be restructured to front-load the resource and key constraints.

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 10 parameters, no output schema, and no annotations, this description is severely incomplete. It fails to explain pagination, the meaning of 'reason' or 'detail_profile', or the structure of the response, leaving the agent with insufficient 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 40%, leaving 6 of 10 parameters undocumented. The description adds no explanation for any parameter, failing to compensate for the schema's gaps.

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

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

The description states it lists job stages, but claims stages are configured on a job while the input schema lacks any job identifier, creating ambiguity. It does distinguish from siblings like list_pipelines but fails to clarify the scope (e.g., all stages or per job).

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_pipelines or list_jobs. No exclusions or contextual hints, leaving the agent without decision support.

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, but it only restates the tool's purpose. It does not mention pagination, read-only nature, rate limits, or what happens without parameters.

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

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

The description is very concise (two sentences) but at the cost of completeness. It is front-loaded but lacks detail needed for effective tool use.

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 10 parameters, low schema coverage, and no output schema, the description fails to cover important aspects like pagination, filtering, and return values. It is insufficient for a complex list 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?

Schema description coverage is only 40%, and the description adds no parameter semantics beyond the schema. Key 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 that the tool lists job status changes for opening lifecycle and approval tracking. It identifies the resource and action, but does not explicitly differentiate from sibling tools like list_job_requisition_status_logs.

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 exclusions or prerequisites mentioned. The description lacks any context for appropriate usage.

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

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

No annotations exist, so the description carries the full burden. It only says 'List members,' implying a read operation, but lacks details on authentication, rate limits, side effects, or response behavior. Parameters like detail_profile suggest response format differences, but these are not explained.

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

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

The description is very short (two sentences), but the first sentence is tautological with the tool name. It lacks necessary detail, 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 10 parameters, nested objects, no output schema, and no annotations, the description is completely inadequate. It does not explain the resource, pagination, filtering, or any parameter purpose.

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 40%, and the description adds no parameter explanations beyond what the schema provides. The description does not compensate for the low coverage, leaving most parameters undocumented.

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 members' with a specific context 'TalentLyft members for recruiter, coordinator, and hiring-team joins,' which distinguishes it from sibling tools like list_candidates. However, it could be more precise about the resource type.

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

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

No guidance on when to use this tool vs alternatives (e.g., list_candidates, list_jobs). The description simply states what it does without 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?

No annotations provided, so description must cover behavior. It only states 'list', implying read-only, but does not mention pagination, rate limits, authentication needs, or any side effects. Most behavioral traits are undisclosed.

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. It is front-loaded with the core action. However, it may be too terse given the complexity of the tool.

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

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

Given 10 parameters, nested objects, and no output schema, the description is critically incomplete. It does not explain return structure, pagination, filtering, or how to use the 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 40% (low), yet the description adds no parameter-level information. It does not explain the purpose of any of the 10 parameters, leaving agents to rely solely on the schema, which itself is incomplete.

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 specifies verb 'list' and resource 'pipelines' with additional context about 'stage-model and conversion analysis', distinguishing it from sibling list tools. However, the phrase is somewhat vague and could be clearer.

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_pipeline or other list tools. There is no mention of preconditions, filters, or 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?

The description implies a read operation ('list') but does not disclose any behavioral traits such as authentication requirements, rate limits, or whether it mutates state.

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 (two short sentences) but lacks structure and essential information, making it under-informative 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?

With 10 parameters, no output schema, and no annotations, the description fails to provide adequate context for correct usage. Missing pagination, return format, and parameter effects.

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 meaning beyond the input schema. It does not mention any parameters or their purpose, despite the schema having 10 parameters with 40% coverage in descriptions.

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

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

The description clearly states the tool lists rejection_reasons and provides context about disposition hygiene. It is distinct from the sibling tool get_rejection_reason which retrieves a single reason.

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 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 provided, so description carries full burden. Only states 'Move' implying mutation, but no details on side effects, reversibility, or required permissions.

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, no unnecessary words, front-loaded with action and resource.

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?

Write tool with 5 generic parameters and no output schema; description fails to explain success/output, errors, or how to structure request. Incomplete for effective use.

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

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

Schema coverage is 100% but parameters are generic (body_json, query_json, etc.). Description adds no specific meaning for this operation, leaving agent unsure how to specify target stage.

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 verb (move), resource (candidate application), and target (TalentLyft stage), distinguishing it from siblings like update_candidate_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 vs alternatives, no mention of prerequisites or conditions. Dry-run parameter hints at preview but not explained.

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 must disclose behavioral traits. Only states 'update', which implies mutation, but no info on idempotence, auth requirements, or what happens on failure.

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 with no waste, but could be slightly more informative 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?

No output schema and no annotations. Description lacks error context, required fields, or typical use cases, leaving a gap 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 coverage is 100% with descriptions for each parameter. Description adds no extra meaning beyond the schema; baseline 3 is appropriate.

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

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

Description clearly states the action (update) and resource (candidate), distinguishing from create/get/list siblings. However, it lacks specificity about which fields or scope, so not a 5.

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

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

No guidance on when to use this tool vs alternatives (e.g., update_candidate_application). No when-not-to-use 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?

No annotations are present, and the description lacks any behavioral details such as side effects, authorization requirements, rate limits, or what happens to existing data. The description adds no transparency beyond the mere action of updating.

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 (one sentence), which could be considered concise, but it is under-specified and lacks necessary detail. It does not earn its place as it provides minimal value beyond the tool name.

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

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

Given the lack of annotations, output schema, and detailed description, the tool is severely incomplete. The agent has no information about return values, error conditions, or the full semantic context of the operation.

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

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

The input schema has 100% description coverage for its 5 parameters, so the baseline is 3. The tool description adds no additional meaning to the parameters; it relies entirely on the schema descriptions, which are already sufficient.

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 candidate application' is a tautology, essentially restating the tool name without providing specificity about what fields or aspects of the application can be updated. It does not differentiate from sibling tools like move_candidate_application_to_stage, which also modifies an 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 usage guidance is provided. The description does not indicate when to use this tool over alternatives, what prerequisites exist, or what context is appropriate (e.g., only after creation, or for specific status changes).

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, and the description does not disclose behavioral traits such as partial vs full update, idempotency, permissions needed, 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, which is too terse given the tool has 5 parameters and complex behavior. It is under-specified, not 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 no output schema, no annotations, and 5 parameters including nested objects, the description is extremely incomplete. It omits behavior, error handling, response format, and any operational 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 coverage is 100%, so baseline is 3. The schema descriptions of parameters are present but vague. The tool description adds no additional parameter meaning, meeting 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 it updates a job, differentiating it from create, get, and list siblings. However, it lacks specificity on what fields can be updated, remaining minimal but adequate.

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 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.