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localharness

An open-source, model-agnostic agent harness for local LLMs. Define agents in YAML (tools, memory, deny-first permissions) and run them against any OpenAI-compatible endpoint: vLLM, Ollama, LM Studio, or llama.cpp.

Best fitUsers who want source-backed project understanding before installing it.

Check whether this project matches your task before installing it.

What it can doskill, recipe, host_instruction, eval, preflight

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot18 stars

1 forks · 2 contributors

Doramagic.ai Last verification date: 2026-07-21 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-07-21

What is localharness?

An open-source, model-agnostic agent harness for local LLMs. Define agents in YAML (tools, memory, deny-first permissions) and run them against any OpenAI-compatible endpoint: vLLM, Ollama, LM Studio, or llama.cpp.
Best fit: Users who want source-backed project understanding before installing it.
Not for: Not for users who want to skip sandbox verification or cannot accept configuration, permission, or maintenance overhead.
Capability added to an AI workflow: skill, recipe, host_instruction, eval, preflight
First safe verification step: Verify the smallest path in an isolated environment and keep a rollback path.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: Developers may fail before the first successful local run: Version banner reads stale install metadata on editable installs — shows old version after every source update
Evidence base: https://github.com/ahwurm/localharness, https://github.com/ahwurm/localharness#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forUsers who want source-backed project understanding before installing it.

Match the project to your task before installing it.

Capabilityskill, recipe, host_instruction, eval, preflight

Repositoryahwurm/localharness

18 stars · 1 forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Overview and System Architecture

Related topics: Memory, Learning, and Recall Pipeline, Agent Loop, Tooling, and Permissions, Deployment, Benchmarking, and Operations

Source: https://github.com/ahwurm/localharness / Human Manual

Memory, Learning, and Recall Pipeline

Related topics: Overview and System Architecture, Agent Loop, Tooling, and Permissions

Source: https://github.com/ahwurm/localharness / Human Manual

Agent Loop, Tooling, and Permissions

Related topics: Overview and System Architecture, Deployment, Benchmarking, and Operations

Source: https://github.com/ahwurm/localharness / Human Manual

Deployment, Benchmarking, and Operations

Related topics: Overview and System Architecture, Memory, Learning, and Recall Pipeline, Agent Loop, Tooling, and Permissions

Source: https://github.com/ahwurm/localharness / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/ahwurm/localharness, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars18 stars

Forks1 forks

Contributors2 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using localharness with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
Zombie docker-run client defeats the managed server's dead-process fail-
github / github_issue
02
Act-guard sentinel echo replaces the user-visible answer with the CONFIR
github / github_issue
03
Version banner reads stale install metadata on editable installs — shows
github / github_issue
04
Contradictory sem/ atoms coexist as active — mined facts never supersede
github / github_issue
05
Turns with an empty memory shelf are never recorded in injection traces
github / github_issue
06
Mid-turn tier-2 input classification is starved by the single-flight inf
github / github_issue
07
Discovery candidates can enter permanent limbo: evidence re-accrual on u
github / github_issue
08
Exiting the REPL immediately after an answer skips that turn's end-of-tu
github / github_issue
09
Turn summary fallback can resurface a PRIOR turn's reply when the model
github / github_issue
10
Discovery candidate tags never progress past 'proposed' — naming/promoti
github / github_issue
11
Write-gate novelty capture re-claims 'first successful use' of the same
github / github_issue
12
remember()-saved memories are never tagged at write time; backfill runs
github / github_issue

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install localharness

Official start command · https://github.com/ahwurm/localharness#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

localharness Manual

Open the full manual

https://github.com/ahwurm/localharness Project Manual
Table of Contents
Overview and System Architecture
Related Pages
Purpose and Scope
High-Level Component Map
Event-Sourced Core
Agent Loop and Turn Lifecycle

Overview and System Architecture

Related topics: Memory, Learning, and Recall Pipeline, Agent Loop, Tooling, and Permissions, Deployment, Benchmarking, and Operations

Source: https://github.com/ahwurm/localharness / Human Manual

Memory, Learning, and Recall Pipeline

Related topics: Overview and System Architecture, Agent Loop, Tooling, and Permissions

Source: https://github.com/ahwurm/localharness / Human Manual

Agent Loop, Tooling, and Permissions

Related topics: Overview and System Architecture, Deployment, Benchmarking, and Operations

Source: https://github.com/ahwurm/localharness / Human Manual

Deployment, Benchmarking, and Operations

Related topics: Overview and System Architecture, Memory, Learning, and Recall Pipeline, Agent Loop, Tooling, and Permissions

Source: https://github.com/ahwurm/localharness / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.

Pitfall Log and verification risks

Doramagic surfaces high-risk items before users treat a candidate capability as verified.

medium

Installation risk requires verification

Developers may fail before the first successful local run: Version banner reads stale install metadata on editable installs — shows old version after every source update

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Configuration risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Configuration risk requires verification

Developers may misconfigure credentials, environment, or host setup: Zombie docker-run client defeats the managed server's dead-process fail-fast