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HackU

Mohit-pjcts/HackU

Background AI agents control real apps via cheap classifier decisions.

Agent Decisions1.00Runner-up: Classification & RoutingGhostwriterFunnelFlight recorder
Automated README summary

Automatically summarized from the README on 3 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

Backstage lets you tell your computer what to do, and coloured AI agents perform tasks inside real apps in background windows while you keep working. It also answers questions about your screen out loud with drawings. For macOS and Windows users.

How it uses Jev

Jev decides each step's action and control in the agent loop (observe, perceive, decide, gate, act, verify). It also picks the app when none is named, and verifies task completion. Its calibrated probabilities are used in code: below 0.4 confidence, the agent stops instead of acting.

Primitives:choicescore

Technique worth stealing

Use a cheap calibrated classifier for per-step decisions, reserving LLM calls for open-ended planning and borderline checks.

Try it

macOS: bash start.sh; Windows: powershell -ExecutionPolicy Bypass -File start.ps1

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-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

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 projectFound in material0.91
  • Shows a System One patternFound in material0.90
  • Describes handling uncertaintyFound in material0.84
  • Reports measured numbersunclear0.56
  • Is a runnable toolFound in material0.85
  • Top-10 learning shortlist signalnot found in the excerpt0.38
  • Is a replica of the modelnot found in the excerpt0.39
  • Solves a common problem (0–2)score on a 0–2 scale1.24 / 2
  • About JevFound in material0.89
Signals
Jev is core to the project0.91Shows a System One pattern0.90Describes handling uncertainty0.84Reports measured numbers0.56Is a runnable tool0.85Top-10 learning shortlist signal0.38Is a replica of the model0.3900.51Solves a common problem (0–2)1.24 / 2012

no-judgment band (0.40–0.60)

Design patterns
Funnel0.94Flight recorder0.83Ghostwriter0.71Blind review0.62Traffic light0.38Menu0.30Grey zone0.30Fail open, fail closed0.26Inspection0.22Check-up0.2200.51

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 3 Oct 2026.