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what is omniagents fr?

lovelogicaillc/omniagents — explained in plain English

Analysis updated 2026-07-25

0HTMLAudience · developerComplexity · 4/5Setup · moderate

tl;dr

A framework for building AI agents that don't stop at the first answer, they keep using every available tool and model until the result meets your quality bar, with human-set budgets and safety controls.

vibe map

mindmap
  root((repo))
    What it does
      Agents that dont stop early
      Works with multiple AI models
      Runs in terminal and browser
    Key concepts
      Effort Governor loop
      Capability Ledger memory
      Verification Gate proof
      Human control budgets
    Use cases
      Long running research tasks
      Multi model workflows
      Quality gated automation
    Tech stack
      Bun runtime
      HTML
      Command line interface
    Ecosystem
      Hermes Council
      Control Plane

Code map

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what do people make with this?

VIBE 1

Build an AI research agent that keeps refining its analysis until it meets your quality standards.

VIBE 2

Create automation workflows that try multiple AI models and tools before giving you a final result.

VIBE 3

Set up task agents with spending limits and kill switches so they stay within your budget.

VIBE 4

Run agents that remember past successes and failures to improve over multiple runs.

what's the stack?

BunHTMLCLI

how it stacks up fr

lovelogicaillc/omniagents100/rutgers-pbl-dining-2015a15n/a15n_old
Stars0
LanguageHTMLHTMLHTML
Last pushed2015-12-012016-06-18
MaintenanceDormantDormant
Setup difficultymoderateeasyeasy
Complexity4/51/51/5
Audiencedevelopergeneralgeneral

Figures from each repo's GitHub metadata at analysis time.

how do i run it?

Difficulty · moderate time til it works · 30min

Requires installing the Bun runtime and configuring API keys for at least one AI model provider.

in plain english

OmniAgents is a framework for building AI agents that are designed to keep working on a task until the result is genuinely as good as it can get, rather than stopping at the first plausible answer. It works with multiple AI model providers, including Claude, GPT, Gemini, Grok, and local models. The core idea is that most agent systems stop too early, producing a single answer and summarizing it, while OmniAgents pushes the agent to use every available tool, skill, and approach before declaring the work done. The framework is built around six rules. An agent must not yield early: it stops only when acceptance criteria are met and no remaining tool or retry would improve the result. The agent must consider the full capability surface, meaning every relevant tool, installed skill, available model, and memory of past successes and failures. Each run produces a capability ledger that records what worked, what failed, and what would be needed to unlock the failed items. This ledger carries forward, so the system remembers its limits and improves over runs. Humans remain in control by setting goals, authority limits, kill switches, and budgets for tokens, money, and time. The system is provider-agnostic, so it is not tied to one vendor, and it operates natively in the operating system, terminal, browser, and filesystem rather than functioning as a chat widget. The architecture centers on an Effort Governor, which runs a loop of planning, acting, observing, recording in the ledger, and replanning. If the agent stalls, it escalates to a stronger model, a different tool, or a human. A Verification Gate requires proof that the deliverable works, such as test output or screenshots, before the agent can declare completion. The code example shows installation via Bun and a command-line interface for running agents against goals and inspecting the ledger afterward. The README also describes a broader ecosystem of related projects under the LoveLogic umbrella, including a multi-agent deliberation layer called Hermes Council and a governance layer called Control Plane. The repo map at the bottom is cut off. The full README is longer than what was shown.

prompts (copy fr)

prompt 1
Using OmniAgents, write an agent config that researches a topic using Claude and GPT, keeps working until the summary passes a verification check, and stops if it spends more than $5 in API tokens.
prompt 2
Set up an OmniAgents goal that automates a file organization task, uses the capability ledger to remember which tools failed last time, and escalates to a human if it gets stuck twice.
prompt 3
Using OmniAgents, create an agent that writes and tests code snippets, running tests as its verification gate, and only reports done when all tests pass.
prompt 4
Configure an OmniAgents run that tries Gemini first, then escalates to Grok if the first model stalls, with a 10-minute time budget and a kill switch I control.

Frequently asked questions

what is omniagents fr?

A framework for building AI agents that don't stop at the first answer, they keep using every available tool and model until the result meets your quality bar, with human-set budgets and safety controls.

What language is omniagents written in?

Mainly HTML. The stack also includes Bun, HTML, CLI.

How hard is omniagents to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is omniagents for?

Mainly developer.

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