gapup-mcp

talent_legal_dashboard

Read-onlyIdempotent

Generates a real-time legal risk dashboard for CHROs, covering contracts, intellectual property, and labor law compliance. Inputs include jurisdiction, employee count, and risk thresholds; outputs include risk scores, actionable alerts, and source citations. Ideal for proactive legal risk management and compliance monitoring. Pass async:true to avoid timeout.

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.
`includeIP`	No
`jurisdiction`	Yes
`employeeCount`	Yes
`riskThreshold`	No
`includeLaborLaw`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`alerts`	No
`status`	Yes
`sources`	No
`warnings`	No
`riskScore`	No
`lastUpdated`	No

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds that the tool is real-time, may time out (hence async option), and lists outputs (risk scores, alerts, citations), providing useful behavioral context beyond the annotations.

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 plus a brief advisory, front-loaded with purpose, and every sentence contributes value. No wasted words.

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 tool's complexity (6 parameters, output schema exists), the description covers purpose, key inputs, outputs, and async usage. It is missing explicit details on optional parameters includeIP and includeLaborLaw, but overall it is sufficiently complete for selection and invocation.

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 low (17%), but the description compensates by naming key inputs: jurisdiction, employee count, risk thresholds, and async. It does not explain includeIP or includeLaborLaw, but these are inferable from the dashboard scope. Overall, it adds meaningful context beyond 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 the tool generates a real-time legal risk dashboard for CHROs, covering contracts, IP, and labor law. This specific verb+resource combination distinguishes it from more focused sibling tools like talent_contract_risk_mapper or talent_litigation_exposure.

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 says it is 'ideal for proactive legal risk management and compliance monitoring,' providing clear context for when to use it. However, it does not explicitly state when not to use it or suggest alternative tools.

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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