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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.
Passed 22 of 22 test cases with the skill, and 6 of 22 without it.
and 17 more in the full report
16 fixed6 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 16 test cases the skill fixed. Same model, same prompt, with and without the skill.
Give us a standard default model selection for routine US case law research when no special constraints or strict requirements are provided. Return PRIMARY, FALLBACK, ESCALATE IF, AVOID, CONFIDENCE, and VERIFY.
| Checked | Without skill | With skill |
|---|---|---|
| Recommends Gemini 3 Flash as the primary default model. | Missed | Passed |
The instructions your model reads when the skill loads.
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.
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.)
Batched, multiple-choice, recommended-first:
Exploratory ·
Working analysis · High — client-facing / filed.Don't care · Balanced · Minimize.Batch fine · Interactive · Real-time.US/EN, cloud OK · Non-US or non-English · Privileged → self-host.Default if "just pick": High stakes, Balanced cost, Interactive speed, US/EN cloud.
LegalBench scorecard (Vals AI, 124 models, updated 2026-07-09). Legal reasoning accuracy across six task types. The top 10 sit inside ~2.9 points — rank is mostly noise; route on cost, speed, constraints.
| Model | Accuracy | Cost In/Out (per M) | Latency | Route it for… |
|---|---|---|---|---|
| Claude Fable 5 | 88.56% | $10 / $50 | 8.96s | Top accuracy, but priciest — reserve for the hardest analysis. |
| Gemini 3.1 Pro Preview | 87.40% | $2 / $12 | 10.06s | Near-top accuracy at a fraction of Fable's cost. |
| Gemini 3 Pro | 87.03% | $2 / $12 | 8.33s | Same, stable release. |
| GPT-5.6 Sol | 86.97% | $5 / $30 | 6.20s | Fast + accurate; good interactive pick. |
| Gemini 3 Flash | 86.86% | $0.5 / $3 | 4.67s | Default / value & speed champion — near-top accuracy, cheapest + fastest in the tier. |
| GPT-5.5 | 86.52% | $5 / $30 | 18.14s | Accurate but slow; batch only. |
| GPT-5.4 (xhigh) | 86.04% | $2.5 / $15 | 27.79s | Slow; avoid interactive. |
| Grok 4.5 | 85.97% | $2 / $6 | 67.88s | ⚠️ Brutally slow — never in a research loop. |
| GPT-5 / GPT-5.1 | ~86% | $1.25 / $10 | 7–19s | Solid mid-cost options. |
Decision rules
test cases passed, vs 6 / 22 without
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