assess-patent-legal-status

SkillDev tools

Lets your agent classify a patent's legal status by jurisdiction and date, flagging uncertainty and conflicting sources.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the assess-patent-legal-status skill

About this skill

Classify observed patent/legal status and flag uncertainty or jurisdiction dependence.

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/assess-patent-legal-status/SKILL.md and read by ahel’s review.

Purpose

Classify observed patent status by jurisdiction and observation date while preserving uncertainty and source dependence.

Input contract

required: [patent_record, jurisdiction, observation_date, status_sources]
optional: [family_events, prosecution_events]
constraints: [status is an observation tied to dated sources, not an undated legal inference]

Procedure

  1. Normalize application, publication, grant, lapse, expiration, and abandonment events.
  2. Align events to jurisdiction and observation date.
  3. Reconcile conflicting source observations and preserve the disagreement.
  4. Emit status, confidence, and unresolved legal-status questions.

Output contract

produces: [status_timeline, jurisdiction_status, source_reconciliation, status_uncertainties]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]

Quality gates

  • Every status is dated and jurisdiction-scoped.
  • Conflicts retain both source records and a reconciliation note.

Failure and counterexamples

Do not infer current validity from a filing event alone or transfer one jurisdiction's status to another.

Provenance map

  • resolved: knowledge-acquisition-legal-status-assessment

Signals

GitHub stars
501
Forks
41
Last commit
Sep 2026
Advanced
Catalog kind
skill
Key
assess-patent-legal-status
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine