HR-ASSIST

by dhanush-ts

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct resource/action: employee management, email, tickets, meetings, and leave. No two tools overlap in purpose, making selection unambiguous.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern in snake_case (add_employee, get_employee_details, create_ticket, schedule_meeting, etc.). No mixed conventions or chaotic naming.
Tool Count5/5
With 12 tools covering multiple HR sub-domains (employee, ticket, meeting, leave, email), the count is well-scoped and appropriate for the server's purpose, neither too thin nor overwhelming.
Completeness4/5
Core workflows are covered: employee creation/retrieval, ticket lifecycle (create/update/list), meeting scheduling/cancellation/list, leave balance/apply/history. Minor gaps exist (e.g., no employee update/delete, no single ticket detail, no leave cancellation) but they are workable.
Average 3.2/5 across 12 of 12 tools scored. Lowest: 1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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Add a glama.json file to provide metadata about your server.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
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.
Conciseness1/5
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.
Completeness1/5
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.
Parameters1/5
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.
Purpose1/5
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.
Usage Guidelines1/5
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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only mentions adding an employee and returning a confirmation, but omits details about side effects, validation, error handling, or permissions. Additionally, it lists manager_id as optional while the schema requires it, creating internal inconsistency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the action, but the parameter list is incomplete and contains an error, meaning not every sentence earns its place. A tighter, accurate enumeration of params would be better.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although the tool is simple, the description fails to mention one required parameter (email) and misstates another (manager_id). For an agent to invoke the tool correctly, it must know all required fields and any constraints, which are not provided here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain each parameter. It covers emp_name and manager_id but omits email entirely, and incorrectly labels manager_id as optional despite being required in the schema. This provides incomplete and misleading information to the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add a new employee') and the system ('HRMS'), matching the tool name. It is distinct from sibling tools like get_employee_details, which retrieve data, and send_email, which handles communications.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 instead of alternatives, nor any prerequisites such as whether an employee must already exist or whether email uniqueness is enforced. The description only states what it does, not the context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full behavioral burden. It implies a write operation but doesn't disclose whether balance is validated, overlapping leave is prevented, or an approval workflow exists. It only mentions a return status message.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the action statement. The parameter list is concise and adds no fluff, though it omits substantive detail that would improve usefulness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-param tool, the description is incomplete given the sibling context. It lacks domain context such as leave types, date validation, approval process, or constraints. The presence of sibling tools about leave balance and history suggests more context is needed to avoid misuse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. The param lines only restate the schema property names ('emp_id' as 'Employee ID', 'leave_dates' as 'List of leave dates') without adding format, constraints, or examples. Minimal value added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Apply for leave for an employee' – a specific verb and resource. It distinguishes itself from read-only sibling tools like get_leave_history and get_employee_leave_balance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites such as checking leave balance or when to prefer get_employee_leave_balance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for disclosing behavioral traits. It only says 'get', implying a read operation, but does not mention potential errors, permissions, side effects, or what happens if the employee ID is invalid. The return line is too vague to count as meaningful transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the core purpose. The additional ':param' and ':return' lines, while non-standard, are concise and add some value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity and an output schema, the description is incomplete for practical use. It lacks usage guidance, behavioral context, and sufficient parameter explanation. The agent would need to infer too much from the tool name alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description only adds 'Employee ID' which essentially repeats the parameter name and title. It does not explain the format, constraints, or requiredness beyond what the schema already shows, offering minimal additional meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Get the leave balance of an employee.' This distinguishes it from sibling tools like get_leave_history and apply_leave, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There is no mention of exclusions, prerequisites, or scenarios where other sibling tools would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only says 'Get the list of meetings' and returns a list, but does not mention whether this includes past/future meetings, canceled meetings, ordering, pagination, or any side effects. The behavior is presumed read-only but never explicitly stated, and no additional context beyond the basic action is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and structured with a param/return docstring format. It contains only the essential information and is easy to scan. The ':param' and ':return' lines are somewhat redundant with the schema and tool name, but they don't add significant clutter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter read tool, the description is minimally viable. The output schema exists, so return values need not be detailed. However, the description omits important contextual details such as the scope of meetings (all time? upcoming only?), whether canceled meetings are included, and any filtering or sorting behavior. These are clear gaps given the sibling tools and potential ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 ':param employee_id: Employee ID' line, but this merely restates the schema's title 'Employee Id' and type 'string'. It doesn't specify the format, source (e.g., from get_employee_details), or any constraints (e.g., required, non-empty). The ':return: List of meetings' is generic. Thus the description provides minimal added meaning over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get the list of meetings scheduled for an employee' with a specific verb ('Get'), resource ('list of meetings'), and intended subject ('employee'). It is easily distinguished from sibling tools like schedule_meeting and cancel_meeting, which are write operations, while this is a read operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives, such as when to use schedule_meeting or cancel_meeting, nor does it mention any prerequisites or exclusions. Usage is only implied by the tool's name and action ('Get list of meetings'), which is not sufficient for an agent to choose it confidently among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the action ('List tickets') and return type, but does not explicitly confirm read-only behavior, side effects, or how the optional parameters affect the result (e.g., whether omitting employee_id returns all tickets).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, with a single purpose sentence and concise parameter/return annotations. It avoids fluff, but is under-informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description leaves ambiguity about the optional parameters: it says 'for an employee' but employee_id is optional, and does not clarify what happens when filters are omitted. It also omits allowed status values. Despite having an output schema, the description is incomplete for a tool with optional filters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides only basic restatements of the parameter names ('Employee ID', 'Ticket status') and marks them optional, adding little meaning beyond the schema. It does not specify allowed status values or the behavior when omitted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('tickets'), and adds scope ('for an employee') with an optional status filter, clearly distinguishing it from sibling tools like create_ticket and update_ticket_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for reading tickets, and mentions the optional status filter, but does not explicitly state when to use this tool versus creating or updating tickets, nor any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description says only that the tool schedules a meeting and returns a confirmation message. It does not disclose prerequisites (e.g., employee existence) or potential side effects like conflict detection.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with its purpose, but the :param lines are redundant with the schema, so they contribute little beyond the summary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations, the description is incomplete: it omits important usage constraints and operational details, making it barely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the :param lines essentially repeat the schema names; the only slight addition is 'python datetime format,' which is already implied by the schema's date-time format. No meaningful semantics are added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Schedule a meeting for an employee'—a clear verb and resource that distinguishes it from sibling tools like cancel_meeting or get_all_meetings_for_employee.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives; it only implies usage through its name and minimal statement. There is no mention of when not to use it or which sibling to prefer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose side effects and behavior. It only states the action and returns a 'Confirmation message,' but does not mention irreversibility, required permissions, or what happens if the meeting does not exist. This is minimal transparency for a mutation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with a single-sentence purpose, followed by a parameter list. Every line earns its place, with no filler or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core operation and parameter semantics, making it usable for a straightforward cancellation. However, it lacks behavioral context (side effects, prerequisites) and usage guidance, leaving gaps especially given the absence of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes docstring-style explanations for all three parameters, clarifying employee_id, meeting_datetime format, and topic optionality. This adds significant meaning beyond the schema titles, especially since schema description coverage is 0%. Minor vagueness in 'python datetime format' prevents a 5.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb+resource statement: 'Cancel a scheduled meeting for an employee.' This unambiguously identifies the tool's function and distinguishes it from siblings like schedule_meeting and get_all_meetings_for_employee.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. The description does not mention when cancellation is appropriate, nor does it reference sibling tools or exclusions. Usage is left entirely to the agent's inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 of behavioral disclosure. It states that the tool updates a status but does not mention whether this is a mutating operation with side effects, whether permissions are required, or what happens if the ticket ID is invalid. The description adds minimal behavioral context beyond the verb 'update'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single clear purpose sentence and two parameter definitions. Every word earns its place, with no redundant or verbose content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with an output schema, the description covers the core purpose and parameter meanings. However, it lacks details on when to use the tool (usage guidelines) and any behavioral side effects or constraints. The presence of an output schema reduces the need to explain return values, but the missing usage and behavioral context keeps it from being fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions, so the description must compensate. It does: it explains ticket_id as 'Ticket ID' and status as 'New status (Open, In Progress, Closed)', explicitly listing valid status values. This adds meaningful meaning beyond the raw schema properties.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update the status') and the resource ('a ticket'), and includes parameter definitions for ticket_id and status. It is distinct from sibling tools like create_ticket and list_tickets, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a ticket's status needs to be changed, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The sibling tool names hint at context but are not referenced.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states that it returns a confirmation message, but does not disclose side effects (e.g., whether it sends emails, notifications, or requires specific permissions) or any constraints such as employee existence or item approval. 'Create' implies a write operation, but the description adds little beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a single purpose sentence followed by a compact docstring-style list of params and return. Every line adds value, with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (3 flat string params, no nested objects) and an output schema exists, so the description does not need to detail return values. It covers the purpose, parameters, and return type, and the use case is clear. However, it lacks any guidance on prerequisites or edge cases, which prevents a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description includes explicit parameter documentation (emp_id, item, reason) with brief meanings (Employee ID, Item requested, Reason for the request). This adds meaningful semantics beyond the raw schema, which only provides titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a ticket') and the specific context ('for buying required items for an employee'). It distinguishes itself from sibling tools because it is the only create operation for tickets, while others are update/list-oriented.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case (purchasing items for an employee) but provides no explicit guidance on when to use this tool versus alternatives like update_ticket_status or list_tickets. There are no stated exclusions or prerequisites, so usage context is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states that the tool returns a list of leave history entries but does not disclose behavior for invalid employee IDs, permission requirements, or potential errors. It is a simple read operation, but the description offers minimal transparency beyond the basic return type.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the main purpose, followed by structured Args and Returns sections. Every sentence adds value; there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter and an output schema (though not shown), the description is sufficiently complete. It states the return type as a list of dicts, which gives the caller a clear idea of the result shape. It doesn't cover edge cases, but for this complexity level, the description is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the only parameter, emp_id, by specifying it is the employee ID for whom leave history is requested. This goes beyond the schema, which only provides the type and title. No other parameters exist, so the description adequately covers the parameter's meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'leave history of an employee', distinguishing it from related sibling tools like get_employee_leave_balance (which retrieves balance) and get_employee_details (which retrieves general employee info). It is concise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given on when to use this tool versus alternatives. The intended usage is implied by its name and description—use it when you need the full leave history of an employee—but it does not explicitly mention exclusions or compare with siblings such as get_employee_leave_balance or apply_leave.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states that the tool returns employee ID and manager ID, which is useful, but it does not disclose behavior for edge cases (e.g., name not found, multiple matches) or confirm that the operation has no side effects. The verb 'Get' implies read-only, but this is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using a single line for the purpose and a clean :param/:return format. Every sentence adds value with no wasted words or repetition of the tool name or schema fields. The structure is easy to scan and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 no annotations, the description covers the core purpose and return values. The presence of an output schema reduces the need to explain return structures in detail. However, it lacks explicit handling of ambiguous name matches or 'not found' behavior, which could be relevant. Overall, it is adequate for basic use but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% coverage, so the description must compensate. It explains the 'name' parameter as 'Name of the employee' and specifies the return values, adding meaning beyond the bare schema. It does not detail format or uniqueness constraints, but it provides enough for basic usage. This partially compensates for the lack of schema-level descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Get employee details') with a defined lookup method ('by name'), and the resource is distinct from all sibling tools (leave, tickets, meetings). It uses a clear verb+resource structure that eliminates ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when employee details are needed, but it does not explicitly state when to use this tool over alternatives or provide exclusions. There is no mention of cases like when the employee name is ambiguous or when to prefer a different lookup tool. Context is implied rather than explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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