Skip to content

Agent Handoff Gate

An experimental specification and offline evaluation kit for delegated coding work: evidence schemas, a gate protocol for PASS and BLOCKED reports, and a Jev integration contract.

Stars
0
Language
Python
License
MIT
Published by
Community
Author
zsoXi
Last verified
Oct 2026

About this project

Agent Handoff Gate is an experimental protocol for delegated coding work. It checks the evidence behind a worker's PASS or BLOCKED report before the result reaches the lead agent, and describes how a controller can authorize one bounded continuation without replacing the lead's final review.

Quoted from the project's README. Read the full README.

Highlights

  • A gate-approved packet is never auto-accepted, merged, deployed or authorised; the lead's final review stays with the lead.
  • If the evaluator is unavailable the gate returns to normal lead review, recording the failed assessment and granting nothing new.
  • Version 0.1.0 ships no controller, sandbox or runtime adapter, and nothing in the quickstart launches agents or calls an API.
  • The integration contract separates low model certainty, insufficient evidence, transport failure and a prohibited action.

Watch out

The measured evidence is thin and the project says so. The historical RelayLedger-40 report records two Jev runs with 38/40 and 37/40 raw labels; at a preregistered top_p threshold of 0.80 each retained 22 decisive assessments with no errors among those on that packet, and a native evaluator run scored 40/40 raw accuracy. The README calls these small-sample observations rather than production reliability or cost-saving claims, notes one baseline reported missing input sections and that both baseline semantic hashes were unresolved, and states the public result files are transcribed from the supplied report with no original API responses included. The English benchmark is a translated edition with a new identity and new hashes, and the historical measurements were not obtained on it. The 0.80 threshold is an experimental example, not a universal safety threshold and not TypeSafe's confidence field. It is an independent project, not an official TypeSafe integration. Copy reviewed against the repository README on 2026-10-04, not from running it.

Questions about this entry

Short answers drawn from the linked project or page.

More Jev resources like this

51GitHub stars
Local LinkedIn recruiting workspace on Browser Use's Jev Ultrafast: Jev screens titles, drives navigation, and assesses profile excerpts against your brief while a live browser stays visible; matches and evidence export as JSON.
Jev Agents & MCP#community#jevbest#catalog-import
33GitHub stars
Codex Skill plus stdlib-only Python CLI that recommends which installed skill to read next for a task, allowing no-skill or uncertain answers and never executing candidates.
Jev Agents & MCP#community#jevbest#catalog-import
72GitHub stars
MCP server over stdio that gives coding agents fourteen Jev judgment tools, turning evidence plus an enumerable question into auto, review, or escalate actions from calibrated probabilities.
Jev Agents & MCP#community#jevbest#catalog-import
Research runtime that pages a large logical tool and context space through a small bounded Jev decision surface with explicit approvals.
Jev Agents & MCP#community#jevbest#catalog-import
14GitHub stars
Opt-in Hermes plugin that routes each turn to one skill: a wide Jev Choice plus request checks gate a narrow fits round, injecting a single ignorable hint line.
Jev Agents & MCP#community#jevbest#catalog-import
LangChain deepagents middleware that replaces SkillsMiddleware with per-turn judging, loading only the SKILL.md files a turn needs so large catalogs stay out of the prompt.
Jev Agents & MCP#community#jevbest#catalog-import
Back to all resources

From the Jev community

Posts from builders shipping with Jev right now.

Follow @typesafeai