patent-claim-mapper

name	patent-claim-mapper
title	Patent Claim Mapper
description	Use when mapping patent claims to products, analyzing patent infringement, or preparing freedom-to-operate analyses. Compares patent claims against product features for biotech and pharmaceutical IP assessment.
author	aipoch
author_url	https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Evidence Insight/patent-claim-mapper
license	MIT
version	0.1.0
execution_mode	open
jurisdiction	general
practice	ip
language	en

Source: https://github.com/aipoch/medical-research-skills

Patent Claim Mapper

Map patent claims to product features for infringement analysis, freedom-to-operate assessments, and competitive intelligence in biotech/pharma.

When to Use

• Use this skill when the task needs Use when mapping patent claims to products, analyzing patent infringement, or preparing freedom-to-operate analyses. Compares patent claims against product features for biotech and pharmaceutical IP assessment.
• Use this skill for evidence insight tasks that require explicit assumptions, bounded scope, and a reproducible output format.
• Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.

Key Features

• Scope-focused workflow aligned to: Use when mapping patent claims to products, analyzing patent infringement, or preparing freedom-to-operate analyses. Compares patent claims against product features for biotech and pharmaceutical IP assessment.
• Packaged executable path(s): scripts/main.py.
• Reference material available in references/ for task-specific guidance.
• Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

• Python: 3.10+. Repository baseline for current packaged skills.
• dataclasses: unspecified. Declared in requirements.txt.

Example Usage

cd "20260318/scientific-skills/Evidence Insight/patent-claim-mapper"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.
2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
3. Run python scripts/main.py with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

• Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.