gapup-mcp

patent_ownership_audit

Read-onlyIdempotent

Audits patent ownership for employees or contractors, identifying gaps where inventors may not have properly assigned patent rights to the company. Designed for CHROs to ensure IP compliance and mitigate legal risks. Inputs: employee/contractor names or IDs, optional date range. Outputs: list of patents, ownership status, flagged gaps, and assignment details. Sources: USPTO PatFT and EPO Espacenet public records. Keywords: patent audit, IP compliance, employee inventions, contractor agreements, CHRO.

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.
`dateRange`	No	Optional date range for patent filings
`employeeIds`	No	List of employee or contractor IDs (optional if names provided)
`employeeNames`	Yes	List of employee or contractor full names to audit

Output Schema

TableJSON Schema

Name	Required	Description	Default
`gaps`	No
`status`	Yes
`patents`	No
`sources`	No
`warnings`	No

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already indicate read-only, open world, idempotent. Description adds output details (list of patents, ownership status, gaps) and data sources (USPTO/EPO), enhancing transparency without contradiction.

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?

Concise, front-loaded with core purpose, then audience, inputs/outputs, sources, and keywords. Every sentence adds value; no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With output schema present, description covers purpose, inputs, outputs, and sources adequately. No apparent gaps for the complexity level.

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 baseline 3. Description summarizes inputs (names/IDs, date range) but doesn't add new semantics beyond what's in 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?

Clearly states the tool audits patent ownership for employees/contractors and identifies assignment gaps. Distinguishes from siblings like patent_landscape by focusing on ownership and compliance, not general landscape.

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?

Explicitly designed for CHROs for IP compliance, with specific sources and keywords. While it doesn't list alternatives, the description provides clear context for when to use it.

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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