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

Annotations are absent, so the description must disclose traits. It confirms a write operation ('add') and a confirmation response, but does not mention any side effects, required permissions, or constraints (e.g., duplicate names, max capacity).

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

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

The description is short and front-loaded with the action, but the redundant ':param' lines add little value given schema. Could be more concise by removing the docstring and integrating parameter hints naturally.

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 an output schema (context signal), the description only says 'returns: Confirmation message', which is vague. It does not explain error states, success indicators, or what the confirmation contains. For a creation tool with three required params, more detail is needed.

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

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

Schema description coverage is 0%, meaning the description must add meaning. The docstring-style parameter notes merely restate the names ('emp_name: takes new employee name') without adding value like format, constraints, or expected values. The required 'email' parameter is not even mentioned in the description.

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

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

The description clearly states the action ('add new employee') and the target system ('hrms system'). No direct sibling tool creates employees, so differentiation is not needed, but the purpose is specific and immediate.

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 any alternative, or what prerequisites (e.g., admin rights) are needed. The description only states the action without usage context.

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

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

No annotations provided. The description only mentions applying leaves and returning a status message, lacking disclosure of side effects, auth needs, or constraints.

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

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

The description is short but uses non-standard colon notation for parameters. It could be more structured and formal.

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 leave applications, the description lacks details on date format, error conditions, or approval processes. Output schema exists but doesn't compensate fully.

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 0%, but the description adds inline parameter docs ('emp_id: ID of an employee', 'leave_dates: List of leave Dates'), providing meaning beyond the schema's titles and types.

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 'Apply for leaves for the employee' with parameters, clearly indicating the action and resource. It distinguishes from sibling tools like get_employee_leaves and get_leave_history.

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 or any prerequisites. Sibling tools for different leave operations exist, so such context would help.

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

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

With no annotations, the description must disclose behavior. It only mentions the action and return of a confirmation message, lacking details on side effects, idempotency, error states, or 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?

The description is brief but contains a typo ('Cnacel') and uses a docstring style with colons that may not be ideal for an AI. It is minimally structured.

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

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

Given no annotations and a simple mutation tool, the description lacks completeness: no error handling, return value details, or relation to sibling tools like schedule_meeting.

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's parameter info contradicts the schema: it marks 'topic' as optional while schema requires it. It also misrepresents 'meeting_date' format (python datetime vs schema's date-time string). Schema coverage is 0%, so description should compensate but instead introduces errors.

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 'Cancel' and the resource 'a scheduled meeting of an employee', distinguishing it from sibling tools like schedule_meeting or get_meetings.

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, prerequisites (e.g., meeting existence), or conditions under which cancellation is valid.

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

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

No annotations provided; the description carries the full burden. It does not disclose behavioral traits like success/failure behavior, authentication needs, or side effects. The return description is vague ('Confiramtion of Ticket Genrated').

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

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

Very short (two sentences plus param list), but contains typos ('Nane', 'Confiramtion', 'Genrated'). The purpose is front-loaded, but the param list largely repeats the schema without adding much value.

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

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

No output schema; the return description is vague. Missing context about prerequisites (e.g., employee existence) and how the ticket creation fits into the larger toolset. With 3 required params and simple types, completeness is lacking.

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 0%, so description must compensate. However, description mentions 'emp_name' while schema has 'emp_id', causing mismatch. Explanations for params are minimal and lack examples or format details.

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

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

The description clearly states 'Create ticket for buying items for the employee', specifying the verb (create) and resource (ticket for buying items). It distinguishes from sibling tools like list_ticket, update_ticket_status, add_employee, etc.

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

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

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, such as whether the employee must already exist, or contrast with other ticket-related tools.

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

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

No annotations are provided, so the description must disclose all behavioral traits. It mentions the output (employee ID or Manager ID) but does not specify side effects, error handling for missing employees, or whether it is read-only. The ambiguous 'or' in output leaves uncertainty.

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 a single sentence and a param line. It is front-loaded with the purpose. However, the structure could be improved by separating the return type.

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 simple tool with one parameter and an output schema, the description is partially complete. It explains the input and basic output, but lacks details like employee details fields (beyond ID/Manager ID), behavior for non-existent names, and edge cases.

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 includes a `:param name:` line explaining the parameter's meaning, adding value beyond the schema which only provides type and title. With 0% schema coverage, this is helpful. However, it could be more detailed (e.g., format).

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 employee details by name, with a specific verb ('Get') and resource ('employee details'). Among sibling tools, it is distinct as a retrieval operation, though no explicit differentiation is provided.

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 add_employee or list_ticket. The description does not mention prerequisites or context.

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

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

No annotations are provided, so the description must carry the full burden. It implies a read operation ('Get') but does not explicitly state safety, idempotency, or any behavioral traits. The return note is confusing ('Remaning or the total number of leaves employee have or left') and lacks clarity.

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

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

The description is short and to the point, but it is poorly structured with a mix of prose and docstring-style comments. The return note has typos ('Remaning', 'retuns') which detract from clarity. It is concise but not well-organized.

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

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

For a simple tool with one parameter and an existing output schema, the description covers the basic purpose. However, it lacks usage guidance, sibling differentiation, and a clear explanation of the return value. The return note attempts to describe the output but is confusing.

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 0%, so the description must compensate. It adds a docstring for emp_id: 'Id of an employee', which provides basic context beyond the schema's 'Emp Id' property. However, this is minimal and does not explain format or constraints.

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 the leave balance of an Employee', which clearly identifies the verb (Get) and resource (leave balance). However, it does not distinguish this tool from the sibling 'get_leave_history', which likely retrieves similar leave data, so it lacks 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 offers no guidance on when to use this tool versus alternatives like 'get_leave_history' or 'apply_leaves'. There is no mention of prerequisites, context, or when not to use it.

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

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

No annotations provided, so description must carry full behavioral disclosure. It only states returns a message, not whether it's read-only, requires auth, or scope of data. Minimal info.

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 but includes unnecessary colons and formatting. Could be more focused, but it's not overly long. Adequate but not efficient.

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

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

Given the simplicity and existence of an output schema, the description missing details about filtering or history scope. Does not differentiate from sibling 'get_employee_leaves' well enough.

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 0%, but description adds ':param emp_id: Id of an Employee', which is slightly more than the schema's title 'Emp Id'. However, it's still minimal and obvious.

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 the history of leaves of an Employee', specifying the verb and resource. It distinguishes from sibling 'get_employee_leaves' by indicating 'history', implying past records.

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 vs alternatives like 'get_employee_leaves' or 'apply_leaves'. The description does not mention context or prerequisites.

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

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

No annotations are provided, so the description carries full burden. It only states it returns a list of meetings, without disclosing side effects, error behavior, or access requirements.

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, using a single sentence plus a docstring, with no redundant 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?

With an output schema present, the description does not need to detail return values. However, it lacks context on error handling and usage constraints, making it minimally adequate.

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 0%, but the description adds value by documenting the parameter with ':param emp_id: ID of the employee', clarifying its purpose beyond the schema's title 'Emp Id'.

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 'list of meetings scheduled for employee', effectively distinguishing it from sibling tools like schedule_meeting (create) and cancel_meetings (delete).

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

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

No explicit guidance on when to use this tool versus alternatives; it relies on implied context. The description does not mention prerequisites or exclusions.

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

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

With no annotations, the description must disclose behavioral traits. It only states it returns a list of tickets, but omits side effects, authentication needs, rate limits, or any schema details. This is insufficient.

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

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

The description is concise (two sentences plus param docs) and front-loaded with purpose. The docstring format is slightly verbose but acceptable.

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, no annotations, and a simple list operation, the description is too minimal. It lacks details on ticket fields, pagination, ordering, or any filtering beyond emp_id and status.

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 parameter meaning via docstring comments for emp_id and status. However, it contradicts the input schema: description marks status as optional, but schema requires it. Also, schema coverage is 0%, so description partially compensates but error reduces 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 the list of the tickets' with a verb and resource. However, it does not distinguish from sibling tools like 'create_ticket' or 'get_employee_details', and the specific scope (tickets for a given employee) is implicit via parameters.

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 'create_ticket' or 'update_ticket_status'. There are no explicit conditions, prerequisites, or exclusions.

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

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

No annotations provided, so description must carry behavioral context. It states 'returns Confirmation Message' but lacks details about side effects (e.g., conflict checking, notifications), permissions, or constraints. Insufficient for a scheduling action.

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

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

Description is short but uses Python docstring format with ':param' syntax, which is unusual for an MCP tool and may confuse AI agents. No wasted words, but formatting is suboptimal for 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 the tool's complexity (3 parameters), the description covers basic action but lacks details about edge cases (e.g., invalid employee, past dates). Output schema exists but is not described beyond a vague 'Confirmation Message'. Incomplete for robust agent usage.

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

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

Schema description coverage is 0%, so description adds minimal meaning: clarifies emp_id as 'ID of the employee', meeting_datetime format as 'python datetime format', and topic as 'Topic of the meeting'. This provides some semantics beyond the schema but is not exhaustive.

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

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

Clearly states 'Schedule a meeting for an employee', which is a specific verb and resource. However, it does not differentiate from sibling tools like get_meetings or cancel_meetings, but the purpose is unambiguous.

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

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

No guidance on when to use this tool versus alternatives. Does not mention prerequisites, when not to use, or how it differs from other meeting-related 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?

Tool has no 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?

Tool has no description.

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?

Tool has no description.

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

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

Tool has no description.

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

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

Tool has no description.

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?

Tool has no description.

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

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

No annotations are provided, and the description only says 'returns : Confirmation message', which is insufficient. No disclosure of idempotency, destructive nature, or other behavioral traits.

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

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

The description is short but includes poorly formatted param lines with typos. It is not well-structured for quick parsing.

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 0% schema coverage, the description is very incomplete. It lacks details on response, required permissions, and error conditions.

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 0%. The description mentions a non-existent param 'emp_id' and provides no explanation for 'ticket_id' or 'status'. No guidance on valid status values or formats.

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 'Update the status of the ticket', which is a specific verb+resource pair. It distinguishes from sibling tools like create_ticket and list_ticket. However, the presence of an incorrect param 'emp_id' (not in schema) slightly reduces clarity.

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

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

No guidance on when to use this tool versus alternatives. No context about prerequisites, side effects, 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.