Agent skill · AI & Agents

route-legal-research

Pick the right LLM for LEGAL RESEARCH & ANALYSIS — issue-spotting, rule application, case/statute analysis, memos, and multi-step agentic research. Vendor-neutral routing grounded in mid-2026 benchmarks (Vals AI LegalBench across 124 models; Harvey Legal Agent Benchmark for agentic work). Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model for legal research / case analysis / a memo", "best AI for legal reasoning", "route this researc

lawve-aigithub.com/lawve-aiGitHub ↗
claude-coderead-onlyNOASSERTION
Install
npx skills add lawve-ai/awesome-legal-skills --skill route-legal-research --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Version: 0.1.0
Allowed tools: -AskUserQuestion-Read
Path: skills/legal-ai-model-router-stephane-boghossian/skills/route-legal-research/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 618
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Route: Legal Research & Analysis You are a **model-routing advisor** for **legal research and analysis** — issue-spotting, rule recall/ application, interpreting statutes and case law, and building memos or multi-step research. You recommend which model to reason with; you don't do the research here. Decision support, **not legal advice**. ## When this applies Issue-spotting · rule application · statutory/case interpretation · legal memos · multi-step ("agentic") research over a matter. (For pulling facts out of docs, use `route-info-extraction`. For assessing a specific contract, use `route-contract-review`.) ## Step 1 — Infer, then ask only what's missing Batched, multiple-choice, recommended-first: 1. **Stakes** — *Recommended: High* for anything advising a client or informing a filing. `Exploratory` · `Working analysis` · `High — client-facing / filed`. 2. **Cost** — `Don't care` · `Balanced` · `Minimize`. 3. **Speed** — *Recommended: Interactive* (research is a loop). `Batch fine` · `Interactive` · `Real-time`. 4. **Jurisdiction / language / privacy** — `US/EN, cloud OK` · `Non-US or non-English` · `Privileged → self-host`. Default if "just pick": **High stakes, Balanced cos

What's inside
Steps it walks through
  1. When this applies
  2. Step 1 — Infer, then ask only what's missing
  3. Step 2 — Route using the scorecard
  4. Step 3 — Output (use this exact shape)
  5. Non-negotiables
Ships with 1 file
  • references/scorecard.md
More from awesome-legal-skills
All skills →
About this skill
What does the route-legal-research skill do?

Pick the right LLM for LEGAL RESEARCH & ANALYSIS — issue-spotting, rule application, case/statute analysis, memos, and multi-step agentic research. Vendor-neutral routing grounded in mid-2026 benchmarks (Vals AI LegalBench across 124 models; Harvey Legal Agent Benchmark for agentic work). Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model for legal research / case analysis / a memo", "best AI for legal reasoning", "route this researc

How do I install it?

Run `npx skills add lawve-ai/awesome-legal-skills --skill route-legal-research --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From lawve-ai/awesome-legal-skills, a repository with 618 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going