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mcp-knowledge

by io.github.getgapup

sabbatical_policy_comparator

Read-onlyIdempotent

Enables CHROs to benchmark their company's sabbatical policies against peer organizations using data from SHRM, Payscale, and Mercer. Inputs include company size, industry, and current policy details. Outputs structured comparison with cost impact analysis, eligibility criteria, and duration benchmarks. Ideal for strategic HR planning and policy optimization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
industryYesIndustry classification code (NAICS)
peerGroupNoList of peer company names for direct comparison
companySizeYesNumber of employees in the company
currentPolicyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
benchmarkNo

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds output details (cost impact analysis, eligibility criteria, duration benchmarks) but does not disclose additional behavioral traits like performance, limitations, or the role of the async parameter. With annotations covering safety and idempotency, the description contributes moderate context.

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 two sentences, front-loading the core purpose and target users. Every sentence adds value: the first defines the tool, the second lists inputs and outputs. No filler or redundancy.

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 adequately covers the main purpose and typical use case for CHROs. However, it omits mention of the async parameter (present in schema) and the optional peerGroup input. Given the complexity (5 parameters, nested objects) and presence of an output schema, the description does not fully prepare the agent for all scenarios, especially asynchronous behavior.

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 description coverage is high (80%+), with all parameters having descriptions in the input schema. The description reiterates the key inputs (company size, industry, current policy) but adds no new semantic detail beyond what the schema provides. It does not clarify the peerGroup parameter or the async parameter's behavior.

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 benchmarks sabbatical policies against peers using specific data sources (SHRM, Payscale, Mercer) and specifies the target user (CHROs) and outputs (cost impact analysis, eligibility criteria, duration benchmarks). It is distinct from sibling tools like executive_comp_peer_benchmark or comp_benchmark_geo_delta, which focus on compensation.

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 says 'Ideal for strategic HR planning and policy optimization,' providing implied context for when to use. However, it does not explicitly state when not to use or suggest alternatives. No exclusions or prerequisites are mentioned, leaving the agent to infer usage from the purpose.

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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TDQS

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

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