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pi-auto-router

lucasamonrc/pi-auto-router

Auto model for pi that classifies each prompt and routes it to your best model.

Classification & Routing1.00Runner-up: Verification & GuardrailsFunnel
Automated README summary

Automatically summarized from the README on 22 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A pi coding-agent plugin that adds an "Auto" model: each prompt is classified by a small decision model and routed to the best-fitting model from the user's own catalog, task fit first, then cost.

How it uses Jev

Jev is an optional classifier (e.g. typesafe/jev-latest) alongside the default Cloudflare Clef. It reads the prompt and decides the task kind, complexity, whether the user requested a specific model, and whether the task changed; the router then picks a model and thinking level from the user's catalog.

Primitives:choicescore

Technique worth stealing

Classify the prompt into task kind and complexity, then route by task fit before cost, keeping follow-ups on the same model for cache warmth.

Try it

pi install git:github.com/lucasamonrc/pi-auto-router, then /route setup and select Auto in /model.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.14.0
Project signals
jev-1.14.0
Category
jev-1.14.0
Pattern tags
jev-1.14.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectnot found in the excerpt0.08
  • Shows a System One patternnot found in the excerpt0.19
  • Describes handling uncertaintynot found in the excerpt0.03
  • Reports measured numbersnot found in the excerpt0.02
  • Is a runnable toolFound in material0.86
  • Top-10 learning shortlist signalnot found in the excerpt0.11
  • Is a replica of the modelnot found in the excerpt0.07
  • Solves a common problem (0–2)score on a 0–2 scale1.12 / 2
  • About JevFound in material0.81
Signals
Jev is core to the project0.08Shows a System One pattern0.19Describes handling uncertainty0.03Reports measured numbers0.02Is a runnable tool0.86Top-10 learning shortlist signal0.11Is a replica of the model0.0700.51Solves a common problem (0–2)1.12 / 2012

no-judgment band (0.40–0.60)

Design patterns
Funnel0.72Thermostat0.55Fail open, fail closed0.2400.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 22 Oct 2026.