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skillbox

kitze/skillbox

Self-hosted, versioned skills library for AI agents with optional Jev recommendations.

Automated README summary

Automatically summarized from the README on 28 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

Skillbox is a self-hosted, versioned skills library for AI agents, built with React, Bun, Hono and PostgreSQL. It provides MCP access, scoped client keys, profiles with grants, and optional task-aware recommendations for teams running their own skills infrastructure.

How it uses Jev

When a user requests recommendations, Skillbox sends task text and authorized active skill descriptions to the configured provider (Vercel AI Gateway, TypeSafe AI, or OpenRouter). Jev scores the bounded skill catalog against the task, and the ranked results are returned to the client. On missing key or failure, it falls back to deterministic search with an explicit reason.

Primitives:score

Technique worth stealing

Bounded catalog scoring with batched evaluation and deterministic fallback on any provider failure.

Try it

Run `bash scripts/skillbox.sh setup` then `bash scripts/skillbox.sh start`, open http://127.0.0.1:4791, and configure a provider key in Settings → Jev recommendations.

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 excerpt0.03
  • Shows a System One patternnot found in the excerpt0.05
  • Describes handling uncertaintynot found in the excerpt0.03
  • Reports measured numbersnot found in the excerpt0.02
  • Is a runnable toolFound in material0.87
  • Top-10 learning shortlist signalnot found in the excerpt0.09
  • Is a replica of the modelnot found in the excerpt0.06
  • Solves a common problem (0–2)score on a 0–2 scale1.23 / 2
  • About JevFound in material0.60
Signals
Jev is core to the project0.03Shows a System One pattern0.05Describes handling uncertainty0.03Reports measured numbers0.02Is a runnable tool0.87Top-10 learning shortlist signal0.09Is a replica of the model0.0600.51Solves a common problem (0–2)1.23 / 2012

no-judgment band (0.40–0.60)

Design patterns
Fail open, fail closed0.93Menu0.28Funnel0.28Inspection0.28Viewfinder0.2500.51

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 28 Oct 2026.