gapup-mcp

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

Name	Required	Description
`async`	No	If 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.
`since`	No	Optional start date for changes (YYYY-MM-DD). Defaults to 7 days ago.
`until`	No	Optional end date for changes (YYYY-MM-DD). Defaults to today.
`jurisdiction`	Yes	ISO 3166-1 alpha-2 country code or ISO 3166-2 state/province code (e.g., 'US-CA', 'FR')

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`changes`	Yes
`sources`	Yes
`warnings`	Yes
`last_updated`	No

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, indicating safe reads. The description adds that the tool returns structured legislative updates with summaries, effective dates, and source links, which provides useful behavioral context beyond the annotations. No contradictions are present.

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 concise sentences plus keywords, front-loaded with the main purpose. No redundant information; every sentence adds value. It is appropriately sized for the tool's complexity.

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?

Given the existence of an output schema, the description adequately explains the output content (structured updates with summaries, effective dates, source links). Annotations cover safety and idempotency. The tool is relatively simple, and the description provides sufficient context for agent decision-making.

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 all parameters described in the input schema. The description mentions jurisdiction and optional date range, aligning with the schema but not adding significant new meaning. The jurisdiction format is already specified in the schema. Baseline is 3, and the description provides marginal additional clarity.

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 purpose: providing daily alerts on new labor law changes by jurisdiction to CHROs. It specifies the input (jurisdiction and optional date range) and output (structured legislative updates with summaries, effective dates, source links). This distinguishes it from sibling tools like 'compliance_monitor' and 'legal_clause_extractor' by focusing on jurisdiction-specific legislative changes.

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 lists use cases such as compliance monitoring, risk assessment, and policy adjustments, providing context for when to use. However, it does not explicitly mention when not to use or compare to alternatives among the many sibling tools. The keywords help infer usage but lack direct exclusions or comparisons.

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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources

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