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mcp-knowledge

by io.github.getgapup

labor_law_alert_geo

Read-onlyIdempotent

Provides CHROs with daily alerts on new labor law changes by jurisdiction (state/country). Inputs include jurisdiction (ISO country/state code) and optional date range. Outputs structured legislative updates with summaries, effective dates, and source links. Useful for compliance monitoring, risk assessment, and policy adjustments. Keywords: labor law, compliance, legislation, jurisdiction, CHRO, HR policy.

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.
sinceNoOptional start date for changes (YYYY-MM-DD). Defaults to 7 days ago.
untilNoOptional end date for changes (YYYY-MM-DD). Defaults to today.
jurisdictionYesISO 3166-1 alpha-2 country code or ISO 3166-2 state/province code (e.g., 'US-CA', 'FR')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
changesYes
sourcesYes
warningsYes
last_updatedNo

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true. Description adds that output includes structured legislative updates with summaries, effective dates, and source links, and implies daily frequency. This provides additional behavioral context beyond annotations.

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?

Description is four sentences, front-loaded with purpose, then inputs, outputs, and keywords. Each sentence adds value; however, the keywords sentence could be integrated, but it's still concise and well-structured.

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?

With output schema present and annotations covering safety, the description provides sufficient context: target user, inputs, output structure (summaries, dates, links), and use cases. Complete for a read-only query tool.

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% with descriptions for all parameters (jurisdiction, since, until, async). Description mentions jurisdiction and date range but does not add new meaning or defaults beyond schema. Baseline 3 is appropriate as schema does the heavy lifting.

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 provides daily alerts on labor law changes by jurisdiction, targeting CHROs. It specifies the verb ('provides'), resource ('labor law changes'), and context (jurisdiction-based), distinguishing it from sibling tools that focus on other HR/legal areas.

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

Usage Guidelines4/5

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

The description mentions the tool is useful for compliance monitoring, risk assessment, and policy adjustments, and lists required inputs (jurisdiction, optional date range). However, it does not explicitly compare to alternatives or provide conditions when not to use, though context is clear.

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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