--- name: import-legal-simulation-patrick-munro description: Use when migrating the Patrick Munro legal simulation methodology into the mini-claude-for-legal format. This import adapter preserves adversarial scenario modelling — moot-court style argument construction, counterparty position mapping, and litigation outcome simulation — mapping it into the standard skill model. Suitable for dispute-risk assessment, negotiation preparation, and legal education contexts across common-law and civil-law jurisdictions. license: MIT metadata: id: import.legal-simulation-patrick-munro category: import jurisdictions: [DIFC, ADGM, UK, UAE, LB, __multi__] priority: P3 intent: [__import__, legal-simulation, dispute-modelling, negotiation, migration] related: [import-mediation-dispute-analysis-jinzhe-tan, import-red-team-verifier-patrick-munro, import-vendor-due-diligence-patrick-munro, casesim-dispute-moot] source: Louis — HAQQ Legal AI (github.com/sboghossian/mini-claude-for-legal) version: "1.0" --- # Import: Legal Simulation (Patrick Munro) ## What it does This import adapter migrates a **legal simulation skill modelled on the Patrick Munro adversarial methodology** into the `mini-claude-for-legal` standard format. The Munro simulation approach treats legal analysis as a structured adversarial exercise: Claude plays both sides — claimant and respondent — constructing the strongest plausible argument for each position, then renders a simulated outcome with reasoning. This is distinct from a standard risk-assessment. The simulation is designed to surface arguments that a skilled opponent would make, preparing the legal team for what they will actually face in negotiation, arbitration, or litigation — rather than what a neutral analysis would highlight. ## Import config | Field | Source mapping | Default if absent | |---|---|---| | `simulation_mode` | Legacy `mode` field | `bilateral` (both sides) | | `forum` | Legacy `forum` or `venue` | `arbitration` | | `governing_law` | Legacy `governing_law` | `DIFC` (Munro's primary jurisdiction) | | `argument_depth` | Legacy `depth` | `full` (all sub-arguments) | | `outcome_confidence` | Legacy `confidence_score` boolean | `true` | | `output_format` | Legacy `format` | `moot_brief` | | `persona` | Legacy `role` | `senior_barrister` | ## Dry-run preview ``` IMPORT PREVIEW — legal-simulation-patrick-munro Source shape : Adversarial legal simulation (Munro methodology) Mode : bilateral (claimant + respondent positions) Forum : arbitration (DIFC default) Governing law : DIFC Depth : full Output : moot_brief (structured argument + simulated outcome) Persona : senior_barrister ``` ## Simulation structure (post-import) ### Step 1 — Claimant's best case - Identify the strongest legal grounds for the claimant - State the cause of action, legal basis, factual support - Anticipate and rebut the respondent's likely defence - Quantify relief sought ### Step 2 — Respondent's best case - Identify the strongest defences and counterclaims - Challenge the claimant's legal grounds - Present alternative factual narrative where applicable - Identify procedural bars (limitation, jurisdiction, standing) ### Step 3 — Simulated outcome - Weigh claimant vs respondent arguments - Apply governing-law doctrine and precedent framework - Render simulated outcome: **Likely to succeed / Uncertain / Likely to fail** - Confidence level: HIGH / MEDIUM / LOW - Key swing factors that could change the outcome ### Step 4 — Strategic implications - Settlement value range (if financial dispute) - Negotiation leverage points for each side - Recommended next steps ## Jurisdictional notes | Jurisdiction | Simulation considerations | |---|---| | DIFC | Common law; DIFC Courts; precedent-based; English Court of Appeal decisions persuasive | | ADGM | Common law; ADGM Courts; highly similar to DIFC approach | | UAE onshore | Civil law; Federal Civil Procedure Code; no formal precedent doctrine | | Lebanon | Civil law + commercial courts; French procedural influences; arbitration via Beirut Chamber | | UK | Litigation vs arbitration path distinct; costs-shifting (loser pays) changes settlement calculus | | KSA | Shariah-based; Board of Grievances jurisdiction; arbitration under Saudi Arbitration Law 34/2012 | ## Use cases - **Pre-litigation risk assessment**: simulate the opponent's arguments before filing or responding to a claim - **Negotiation preparation**: identify the counterparty's leverage points before entering settlement talks - **Deal red-teaming**: stress-test contractual positions from the other side's perspective - **Legal education / moot preparation**: practise argument construction with AI-powered opposition ## Failure modes | Error | Likely cause | Resolution | |---|---|---| | `single_sided_output` | Source only modelled one party | Override `simulation_mode: bilateral` | | `governing_law_mismatch` | DIFC config used in civil-law context | Override `governing_law` and note doctrinal differences | | `outcome_overconfident` | Legacy assigned HIGH confidence broadly | Calibrate: most disputes are `MEDIUM` confidence; flag swing factors | | `facts_insufficient` | Sparse fact pattern | Request additional context before running simulation | ## Related skills - [[import-mediation-dispute-analysis-jinzhe-tan]] - [[import-red-team-verifier-patrick-munro]] - [[import-vendor-due-diligence-patrick-munro]] - [[casesim-dispute-moot]] - [[review-legal-risk-generic]]