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mcp-hr-knowledge-evals

mcp-hr-knowledge-evals

by mellowMike92
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

query_hr_policy

Search HR policy handbooks by keyword or meaning and return verified policy text with citation IDs for grounded answers. Filter results by department when needed.

Instructions

Search the HR policy handbook with keyword/semantic matching. Returns verified policy text with citation ids for grounded answers.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "query_hr_policy"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesNatural-language HR policy question
departmentNoOptional department scope filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full disclosure burden. It usefully discloses the matching strategy and that results include citation ids for grounding, but says nothing about result limits, ranking, behavior on zero hits, 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.

Conciseness4/5

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

Two tight sentences, front-loaded with the search action and followed by the return contract. No filler or redundant restatement of the tool name.

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 two-parameter read tool with no output schema, the description adequately covers what the tool does and what it returns, including citations. Missing only edge-case and result-set guidance, which is minor at this complexity.

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

Parameters3/5

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

Schema coverage is 100%, so both parameters are already documented in structured fields, which sets the baseline at 3. The description implies the query is natural-language semantic text, but adds no syntax, formatting, or department-filter nuance beyond the schema.

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

Purpose4/5

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

States a specific verb and resource ("Search the HR policy handbook") plus the retrieval modality (keyword/semantic) and the return contract (policy text with citation ids). It is clearly distinguishable from the sibling tools, but it never explicitly contrasts itself with them.

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?

Usage is only implied by the resource name — an agent can infer this is for HR policy questions. There is no explicit when-to-use/when-not-to-use statement, no mention of alternatives, and no prerequisites such as department scoping rationale.

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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