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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
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.
endDateNoFilter patents filed before this date (YYYY-MM-DD)
startDateNoFilter patents filed after this date (YYYY-MM-DD)
employeeIdNoInternal employee ID (optional if name provided)
companyNameYesExact legal name of company for assignment check
employeeNameYesFull name of employee to track (e.g., 'John Doe')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
patentsYes
sourcesNo
warningsYes
employeeIdNo
companyNameYes
employeeNameYes
totalPatentsYes
unassignedPatentsYes

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering the safety profile. The description adds context about data sources and return fields, but does not disclose potential caveats such as data latency, completeness limitations, or external API dependency. No contradiction with 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?

The description is concise and front-loaded with the target user and core purpose. The keyword list at the end is slightly redundant but does not detract significantly. Each sentence contributes meaning.

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?

For a read-only lookup tool with rich annotations and 100% schema coverage, the description provides sufficient context: what it does, who it's for, input approach, and output contents. It is functionally complete, though a note on result size or pagination would strengthen it.

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 parameters are already well-documented. The description restates that employeeName or employeeId can be used and mentions companyName for assignment checking, but adds little beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool tracks employee patent filings and flags unassigned inventions, specifying the data sources (USPTO/WIPO) and output (assignment status, filing dates, ownership gaps). This is specific and actionable, though it does not explicitly differentiate from sibling tools like patent_ownership_audit.

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

Usage Guidelines3/5

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

The description mentions use cases ('IP audits, inventor onboarding, compliance checks') and target audience (CHROs), providing some context. However, it lacks explicit guidance on when not to use this tool versus alternatives, and no sibling tools are referenced.

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

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.