skills/legal/notice-of-prior-art/SKILL.md
Drafts a Notice of Prior Art disclosing references material to patentability under 35 U.S.C. §§ 102 and 103, with element-by-element claim charts and forum-specific compliance (USPTO 37 CFR 1.56, district court local patent rules, PTAB 35 U.S.C. § 311). Use when preparing invalidity contentions, duty-of-disclosure filings, inter partes review petitions, or pre-litigation prior art disclosures.
npx skillsauth add casemark/skills notice-of-prior-artInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Drafts a litigation-ready Notice of Prior Art with element-by-element claim mapping, prior art reference disclosures, and procedural compliance for USPTO, district court, or PTAB proceedings.
Determine before drafting:
| Forum | Required Elements | |---|---| | USPTO | Application/patent number, art unit, examiner, confirmation number, customer number | | District Court | Full case caption, civil action number, court/division, assigned judge | | PTAB | Proceeding number (IPR/PGR), patent number, petitioner/patent owner |
Include statutory basis (35 U.S.C. §§ 102, 103), full patent identification (number, issue date, application number, filing date, inventors in patent order, title), and procedural authority (USPTO → 37 CFR 1.56; district court → local patent rules; PTAB → § 311).
For each reference, provide:
Patent references:
Non-patent literature:
Public use / on-sale bar (§ 102(a)/(b)):
For each challenged claim, create an element-by-element chart:
| Claim Element | Prior Art Disclosure | Citation (col:line / page:para) | |---|---|---| | [Limitation] | [Corresponding disclosure] | [Precise location] |
Apply the Graham v. John Deere Co., 383 U.S. 1 (1966) framework:
| Graham Factor | Analysis | |---|---| | Scope/content of prior art | Technical field, problems addressed, solutions disclosed | | Level of ordinary skill | Education, experience, technology sophistication | | Differences from prior art | Map references to limitations; identify alleged inventive step | | Motivation to combine | Per KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398 (2007) — from references, skilled-artisan knowledge, or nature of problem | | Reasonable expectation of success | Why a skilled artisan would predict the combination works |
Address secondary considerations if applicable (Stratoflex, Inc. v. Aeroquip Corp., 713 F.2d 1530 (Fed. Cir. 1983) [VERIFY]):
| Exhibit | Description | Date | Source | Relevance | |---|---|---|---|---| | A | [Doc type & title] | [Date] | [Author/source] | [Claim/limitation addressed] |
State whether prior art anticipates (§ 102), renders obvious (§ 103), or raises substantial patentability questions. In litigation, note the clear-and-convincing-evidence standard (35 U.S.C. § 282).
| Forum | Certification | |---|---| | USPTO (37 CFR 1.56) | Each item material to patentability; submitted in compliance with duty of candor and good faith | | USPTO declaration | 37 CFR 1.68 (domestic) or 28 U.S.C. § 1746 (foreign declarants) | | District court | Per local rules and FRCP requirements | | PTAB | Per 37 CFR 42 requirements |
Signature block: typed name, designation (patent attorney/agent), USPTO registration number, firm, address, phone, email, date. Comply with e-filing requirements (Patent Center / CM/ECF).
[VERIFY]Key changes from the original:
>- block with clearer trigger guidance[VERIFY] markersPlease grant file write permission and I'll apply the edit, or you can copy the content above directly.
development
name: automated-contract-summary language: en description: Generates structured executive summaries of contracts using ML — captures key terms, party obligations, risk allocations, and compliance requirements in a standardized format. Optimized for high-volume review where speed and consistency matter. tags: - summarization - agreement - corporate --- # Automated Contract Summarization Produces standardized executive summaries of contracts using machine learning, capturing essential term
tools
Extracts regulatory obligations from dense regulations across jurisdictions. Breaks down multi-level regulations into clear article-level obligations, classifies applicability to a business, and prioritizes by risk level. Use when translating regulations into actionable compliance requirements.
development
Continuously monitors regulatory landscapes for changes relevant to a specific business. Ingests global regulatory updates, filters by relevance, summarizes impact, and produces an actionable change advisory. Use when tracking regulatory developments affecting a particular product or market.
testing
Compares an organization's existing compliance controls, policies, and procedures against extracted regulatory obligations to identify coverage gaps. Produces a remediation plan with prioritized actions. Use when assessing compliance maturity or preparing for regulatory audits.