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ThomasMoreAI/legal-skills-open

Extracts and reconciles medical provider, wage-loss, and insurance/lien data from personal injury plaintiff fact sheets and initial disclosures against builder draft responses. Use when the user mentions PFS analysis, medical provider reconciliation, wage loss audit, insurance lien tracking, PI discovery reconciliation, builder response validation, MDL plaintiff data extraction, FRCP 26(a)(1) disclosures, treatment chronologies, or specials spreadsheets.

What is legal-skills-open?

legal-skills-open is a Claude Code agent skill that extracts and reconciles medical provider, wage-loss, and insurance/lien data from personal injury plaintiff fact sheets and initial disclosures against builder draft responses. Use when the user mentions PFS analysis, medical provider reconciliation, wage loss audit, insurance lien tracking, PI discovery reconciliation, builder response validation, MDL plaintiff data extraction, FRCP 26(a)(1) disclosures, treatment chronologies, or specials spreadsheets.

Works with~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/ThomasMoreAI/legal-skills-open/tree/HEAD/us/personal-injury/skills/pfs-analyzer

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Documentation

PFS Analyzer

Extracts structured data from PI plaintiff fact sheets and initial disclosures, reconciles against draft builder responses, and produces an issues memo with variance flags and full source traceability.

All output requires attorney review before service or filing.

Quick Start

  1. Gather source documents (PFS, provider lists, wage docs, insurance disclosures, builder draft)
  2. Extract providers, employers, and insurance/lien entities with source citations
  3. Reconcile extractions against builder draft — flag all variances
  4. Deliver builder-ready output + lawyer-facing issues memo

Intake Checklist

Ask every time unless user says "use defaults" or "just draft":

  1. PFS / Initial Disclosures — executed PFS, FRCP 26(a)(1) packet, or MDL CMO form
  2. Medical provider list — specials spreadsheet, treatment chronology, HIPAA auth list
  3. Wage loss package — employer verification, pay stubs, W-2s, tax returns
  4. Insurance disclosures — EOBs, PIP/MedPay, lien letters, subrogation notices, Medicare/Medicaid status
  5. Client intake notes — internal questionnaires with details possibly omitted from PFS
  6. Draft builder responses — discovery responses to validate
  7. Forum/jurisdiction — federal vs. state court
  8. Key context — DOI, prior injury history, date range, cash-pay/LOP/workers' comp, pharmacy list, employment gaps >6 months

Defaults (if user doesn't respond): federal court, FRCP 26(a)(1) framework, all available docs, partial output if incomplete.

If any source is missing, label output "Partial" and identify what is absent.

Core Workflow

1. Build Extraction Map

Every extracted data point must include:

FieldFormat
Source document"Doc 1, p. 4" or Bates range
Verbatim textExact wording from source
ConfidenceHigh (explicit with address + dates) / Medium (listed, missing details) / Low (inferred, needs verification)

Rules:

  • Untraceable facts must not be presented as extracted data
  • Preserve spelling in verbatim_name; create separate normalized_name
  • Never silently correct spelling, expand abbreviations, or merge duplicate-looking entities
  • Distinguish treatment facility from billing entity

2. Extract Medical Providers

Per provider, capture: name (verbatim + normalized), type (hospital/clinic/physician/PT/imaging/pharmacy/lab/ambulance), address/phone/fax, service dates, NPI, records/bills status, category (injury-related / pre-existing / billing-lien), source citation.

Rules:

  • Pre-DOI treatment → "Prior/Pre-existing" (never omit)
  • Separate radiology reads, pathology, facility fees as distinct billing entities
  • Referrals are not treatment encounters
  • Do not collapse multiple locations of a provider network
  • Flag potential non-retained treating experts
  • Include pharmacies, PTs, imaging, labs — not only physicians

3. Extract Employment & Wage Loss

Per employer, capture: legal name (+ DBA), address/contacts, job title/schedule/pay rate (exact phrasing), start/end dates, wage documentation, injury impact (first missed date, total days, PTO, return status), benefits applied for (STD/LTD/SSDI/workers' comp).

Rules:

  • Preserve vague references as "reported estimate per disclosure"
  • Distinguish employer from worksite (staffing agencies)
  • Capture self-employment separately
  • Flag mitigation issues and employment gaps

4. Extract Insurance, Liens & Prior Claims

Per entity, capture: insurer/lienholder name (verbatim), plan type, member/group/claim/policy IDs (distinguish each), named insured, contact info, lien status (asserted/pending/final + amount), source citation.

Rules:

  • Extract only what documents contain — never guess limits, coverage, or validity
  • Letter of protection is not an insurance lien
  • Silent on Medicare → flag: "Confirm Medicare beneficiary status and SSDI; may trigger MSP reporting"
  • Capture prior accidents/claims/settlements; flag for builder consistency

5. Reconcile Against Builder Draft

Three-dimension diff:

DimensionCheckFlag
CompletenessEntity-by-entity"Missing in builder" / "New — confirm supplementation"
ConsistencyNames, dates, amounts"Spelling mismatch" / "Date conflict" / "Amount discrepancy"
CharacterizationBuilder vs. disclosure"Overstates" / "Understates"

Priority levels:

  • RED ALERT — Document contradictions (e.g., PFS says not working but records reference work). Requires attorney intervention before service.
  • HIGH — Undisclosed prior accidents, missing providers, inconsistent injury mechanism
  • MEDIUM — Spelling variations, missing addresses, incomplete date ranges
  • LOW — Formatting issues, optional fields unpopulated

Rules:

  • Never silently overwrite builder data
  • Distinguish "disclosed but not produced" from "entirely undisclosed"
  • Do not override intentional attorney scope narrowing — flag and defer
  • Note FRCP 26(e) supplementation timing (state analogs may be stricter)

6. Deliver Output

A. Builder-Ready Output: Separate verbatim_name/normalized_name, include source_citation and confidence per record, match builder schema, include reservation language.

B. Issues Memo (label: DRAFT — Attorney Work Product / For Counsel Review Only):

  1. Client follow-up questions
  2. Supplementation needs with timing
  3. Defense focus areas and impeachment vectors
  4. Red flags with recommended action
  5. Entity verification results (NPI checks)
  6. Privilege flags — exclude attorney-client communications from extraction

Post-Draft Check

Ask after delivering initial output:

  1. Are RED ALERT/HIGH flags accurate — known explanations to incorporate?
  2. Providers/employers client mentioned but absent from disclosures?
  3. Generate supplementation timeline from identified gaps?
  4. Builder schema match confirmed?

Default: address RED ALERT items first.

Quality Checklist

  • Every field has source citation or labeled "client to confirm"
  • Forum-specific law references match actual jurisdiction
  • Provider names checked against CMS NPI Registry; unverifiable names flagged
  • Treatment dates consistent with DOI; pre-DOI marked "Prior"
  • Date formats consistent; no false precision from estimates
  • Identifiers transcribed accurately; OCR-sourced values flagged
  • All provider types included (pharmacies, PTs, imaging, labs)
  • No omission construable as concealment (adversarial review)
  • Builder output matches schema constraints
  • All variances shown — nothing silently overwritten

Compliance Guardrails

  • ABA 1.1/1.3: Attorney must verify; LLM extraction does not satisfy competence/diligence
  • Model Rule 1.6: Mask identifiers in memo (last four only); full values in secure builder fields
  • Model Rules 3.3/3.4/4.1: Distinguish documented facts from reported estimates; never assert completeness if record is incomplete
  • FRCP 37: Incomplete provider lists are common sanctions targets
  • HIPAA: All extracted data is PHI; handle per firm protocols
  • Conflicts: Multiple potential claimants → flag for Model Rule 1.7 screening
  • Anti-hallucination: Every data point traceable to source; never invent names, dates, identifiers; unverified citations must be flagged

Jurisdiction Notes

  • Federal MDL: Follow CMO-mandated PFS headers exactly; non-compliance risks dismissal
  • California: CCP governs; plaintiff verification form required
  • Florida: Align with Form 1.977 interrogatories (10-year history) [VERIFY]
  • Texas: Map to Rule 194 Required Disclosure categories [VERIFY]
  • State auth forms: Flag "state-specific medical authorization — attorney to confirm"

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

ThomasMoreAI/legal-skills-open

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ThomasMoreAI/legal-skills-open

When the user's message starts with "Canada" (case-insensitive), generate a full Ontario PI Case Assessment Memo from the case_stressor corpus and return it verbatim. This is the primary handler for Canadian fact patterns — DO NOT ask clarifying questions first; run the memo and let the lawyer react.

ThomasMoreAI/legal-skills-open

交通事故责任评估与判定专业技能。当用户需要交通事故责任分析、事故现场照片评估、交通法规咨询、事故责任划分、法律依据查询时触发此技能。适用于车辆碰撞事故、行人事故、非机动车事故等各类道路交通事故的责任认定场景。无论用户使用"交通事故"、"车祸"、"责任判定"、"交通法规"、"事故定责"等何种表述,只要涉及交通事故评估或责任认定,均应调用此技能。

ThomasMoreAI/legal-skills-open

Strategische Markenportfolio-Planung für Luxus-Modehaeuser: Mandant will Marken in DE/EU/international schützen oder Portfolio optimieren. Normen: §§ 32 ff. MarkenG, Art. 32 ff. UMV (EU) 2017/1001, Madrid-Protokoll (WIPO). Prüfraster: Nizza-Klassen (3/14/18/25/35), Multi-Class-Strategie, Prioritaets-Kaskade, Kostenoptimierung, Anmeldezeitpunkt. Output Marken-Portfolio-Plan, Anmelde-Empfehlung je Territorium, Kostenprojektion. Abgrenzung: Einzelne Anmeldung DPMA siehe wortmarke-anmeldung-dpma; Madrid-Protokoll Details siehe madrid-protokoll-und-internationale-registrierung.

ThomasMoreAI/legal-skills-open

Audit an intellectual-property portfolio for ownership, protection, scope, deadlines, territorial coverage, use, value, encumbrances, and enforcement risk. Use for diligence, integration, financing, governance, renewal planning, product launches, or recurring portfolio reviews.

ThomasMoreAI/legal-skills-open

Use whenever the user asks about a motor-vehicle statute, citation, contributing factor, OR a Canadian personal-injury fact pattern — always query Specter's Harvester API before answering. The API auto-routes between two collections (US statutes + Canadian PI case law).

ThomasMoreAI/legal-skills-open

Assesses product liability exposure on given facts — classifying the defect as manufacturing, design, or warning/instruction, mapping which party in the supply chain is potentially exposed, and grading the realistic exposure. Use this whenever a user wants product liability worked through rather than a general deficiency test — including phrasings like "what's our exposure if this product injured someone", "is this a design defect or a manufacturing defect", "who in the supply chain is on the hook here", "assess our product liability risk on these facts", or "how exposed are we if the warning label was inadequate". Distinct from deficiency-analyst, which tests service and trade-practice thresholds — this is specific to defective products and supply-chain exposure. Fires for any product liability question, in any jurisdiction, for manufacturers, assemblers, sellers, distributors, or importers.

ThomasMoreAI/legal-skills-open

KI-VO Hochrisiko-Anforderungen für Personalwesen in Kanzleien ab August 2026: Anwendungsfall Kanzlei setzt KI im HR-Bereich ein oder beraet Mandanten zum AGG-konformen KI-Einsatz bei Bewerberauswahl. Anhang III Nr. 4 KI-VO Hochrisiko Bewerberauswahl, Inkrafttreten 2. August 2026, AGG Diskriminierungsverbot. Prüfraster Hochrisiko-Klassifizierung eigener HR-KI, Konformitätsbewertung, Transparenzpflichten für Betroffene, Beratungsmandate Arbeitsrecht. Output Checkliste Hochrisiko-Anforderungen mit Umsetzungsplan für August 2026. Abgrenzung zu Bias-und-Diskriminierung-Prüfung und zu KI-VO-Betreiber-Pflichten.

ThomasMoreAI/legal-skills-open

Vorlagetabelle für Portfolio-Review von Arbeitsvertraegen im 3D-Format: Forderung/Prüfung/Stellung. Normen: BGB, KSchG, ArbZG. Prüfraster: Vertragsbedingungen, Klauselgueltigkeit, HR-Compliance. Output: Arbeitsvertrag-Portfolio-Tabelle. Abgrenzung: nicht allgemeine 3D-Review-Konfiguration.

ThomasMoreAI/legal-skills-open

Unternehmen oder Kanzlei muss IP-Portfolio verwalten und anstehende Fristen im Blick behalten. Schutzrechtsportfolio-Verwaltung. Prüfraster: Eintragungen Verlaengerungen Jahresgebühren Benutzungsnachweise Fristkalender. Output: Fristenkalender und Portfolio-Audit mit Luecken Verfall und Benutzungsfragen. Abgrenzung zu schutzschrift-eilverfuegung (Verletzungsverteidigung) und markenanmeldung-dpma.

ThomasMoreAI/legal-skills-open

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ThomasMoreAI/legal-skills-open

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ThomasMoreAI/legal-skills-open

Strukturierte Prüfung von Ansprüchen wegen Behandlungsfehler nach §§ 630a ff. BGB iVm § 823 BGB. Behandlungsvertrag Aufklärungspflicht § 630e BGB Dokumentationspflicht § 630f BGB Beweislastregeln § 630h BGB grober Behandlungsfehler Beweislastumkehr voll beherrschbares Risiko Anfaengerstandard Schmerzensgeld § 253 BGB. Schlichtungsstelle Aerztekammer MDK-Gutachten. Verjährung drei Jahre § 195 BGB Hoechstfrist dreissig Jahre § 199 Abs. 2 BGB.

ThomasMoreAI/legal-skills-open

Workflow-Skill zu fachanwalt medizinrecht aufklaerungsfehler. Nutzt Normtext, Nutzerangaben und verifizierte Quellen; Rechtsprechung nur nach Live-Pruefung mit Gericht, Datum und Aktenzeichen.

ThomasMoreAI/legal-skills-open

Behandlungsfehler §§ 630a 630h BGB Verletzung medizinischer Standard. Diagnosefehler Therapiefehler Befunderhebungsfehler Hygienefehler. Beweisregeln § 630h BGB Vermutung Kausalität bei grobem Behandlungsfehler § 630h Abs. 5 BGB Befunderhebungsfehler Dokumentationsmangel. Schadensersatzanspruch §§ 280 823 BGB Schmerzensgeld § 253 BGB. Verjährung drei Jahre § 195 BGB ab Kenntnis 30 Jahre Hoechstfrist.

ThomasMoreAI/legal-skills-open

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ThomasMoreAI/legal-skills-open

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ThomasMoreAI/legal-skills-open

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ThomasMoreAI/legal-skills-open

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ThomasMoreAI/legal-skills-open

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