gapup-mcp

ip_employee_invention_tracker

Read-onlyIdempotent

For CHROs: tracks employee patent filings and flags unassigned inventions. Input employee name or ID to retrieve their patent applications from USPTO and WIPO databases. Returns list of inventions with assignment status, filing dates, and potential ownership gaps. Useful for IP audits, inventor onboarding, and compliance checks. Keywords: patents, IP ownership, employee inventions, USPTO, WIPO.

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.
`endDate`	No	Filter patents filed before this date (YYYY-MM-DD)
`startDate`	No	Filter patents filed after this date (YYYY-MM-DD)
`employeeId`	No	Internal employee ID (optional if name provided)
`companyName`	Yes	Exact legal name of company for assignment check
`employeeName`	Yes	Full name of employee to track (e.g., 'John Doe')

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`patents`	Yes
`sources`	No
`warnings`	Yes
`employeeId`	No
`companyName`	Yes
`employeeName`	Yes
`totalPatents`	Yes
`unassignedPatents`	Yes

TDQS

A4.2/5.0

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 behavioral context beyond these, such as the output includes 'assignment status, filing dates, and potential ownership gaps', and the databases queried. No contradictions.

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 four sentences with no extraneous text. It front-loads the main purpose and uses keywords efficiently. Every sentence adds value.

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 richness of annotations (readOnly, openWorld, idempotent) and the presence of an output schema, the description provides adequate high-level context about inputs, behavioral queries, and return format. It could mention the date filtering parameters, but overall it's complete enough.

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 100%, so the schema already documents all parameters well. The description mentions 'employee name or ID', matching the schema, but does not add additional meaning beyond the schema for the date filters or other parameters. Baseline 3 is appropriate.

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 uses specific verbs ('tracks', 'flags', 'retrieve') and clearly identifies the resource ('employee patent filings', 'USPTO and WIPO databases'). It distinguishes the tool's employee-specific scope from broader sibling tools like patent_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?

The description targets a specific user ('For CHROs') and lists concrete use cases ('IP audits, inventor onboarding, compliance checks'). However, it does not explicitly state when not to use this tool or mention alternatives among the many sibling 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.

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