From requirement intake to implementation, review, documentation, and deployment — every phase as a versioned skill, running inside your own agent runtime.
One package carries a complete, AI-assisted delivery process: every phase of a user story's life runs as a versioned, reviewable skill — as a slash command directly in your agent runtime (/help lists the full catalog).
Meeting transcripts become structured Jira stories with acceptance criteria.
Codebase analysis produces reviewable implementation notes.
AI-generated first drafts with tests — in the customer's own tech stack.
Rubric-scored reviews, PR tooling, and deterministic test data.
Environment promotion, release notes, and documentation.
From drafting stories out of meeting transcripts and implementing whole epics in parallel to release pull requests and architecture documentation — every workflow step is a slash command.
Skills, adapters, and a Node installer — no CloudRise server in the loop, no telemetry, no phone-home. Your code, tickets, and transcripts never leave your environment.
Semantic versioning with VERSION, CHANGELOG, and immutable releases. Every skill execution leaves a schema-validated log — auditable in your own repository.
No skill contains a customer name, a vendor tool, or a runtime primitive. Five independent axes are resolved from configuration when a skill executes — a new platform, runtime, or git strategy is a new adapter document, never a fork of the skills.
Identity, credentials, naming conventions, locale, and paths — your own configuration repository, linked at install time.
Stack-specific commands and standards — Salesforce, Node/Cloudflare, and more. Platform-specific skills abort cleanly where they do not apply.
Claude Code, OpenAI Codex, Gemini CLI, local LLM, or a hosted endpoint — switchable per run, with cross-runtime review.
Cloud (MCP tools) or Data Center (REST with a token) — the same Jira and Confluence workflows in both worlds.
Feature-branch, trunk-based, or gitflow — branching, PR gates, and story promotion follow your model.
The skills exist exactly once — and run natively where you work. Data-sovereign too: with a local LLM or a European endpoint of your choice as the data perimeter.
Full capability: parallel subagents, worktree isolation, MCP, web search.
Native skill execution with reduced parallelism.
Native MCP, sequential processing.
Ollama / llama.cpp — for privacy and offline scenarios.
Any OpenAI-compatible endpoint — e.g. Scaleway, OVHcloud, IONOS, STACKIT. The API key never enters configuration, only the name of its environment variable.
A weighted scoring rubric with a 100-point scale and banded thresholds. A hard severity gate still governs go/no-go — the score is the auditable summary.
Every skill announces its scope before doing anything else. Platform and runtime guards abort cleanly instead of guessing. Secrets never enter configuration.
Each skill execution writes a schema-validated JSON log into your own repository — skill, story, runtime, status, and artifacts are answerable at any time.
The harness and your configuration repository are both private. Onboarding sets up two access grants — verify both once per machine before installing.
cloudrise-license.json — delivered together with your invoice@aethon-x/harness is a private npm package. Your npm account is invited to the aethon-x organization; after that, a single npm login per machine is enough. Important: without access, npm reports 404 Not Found — that is npm hiding a private package, not a wrong package name. If you are missing the invite, contact CloudRise.
On first run, harness init clones your configuration repository — from GitHub by default. If it lives elsewhere (your own GitHub organization, GitLab, Bitbucket, an internal git server), point the environment variable PIPELINE_CUSTOMER_REPO_URL at any git URL for the first init. Afterwards the repository updates via a plain git pull.
npm install --save-dev @aethon-x/harnessPut the cloudrise-license.json you received into the project root (or into ~/.config/cloudrise/). Validation runs offline via an Ed25519 signature — nothing is transmitted.
harness init clones and links your configuration, selects runtime and git strategy, and makes the skills available as slash commands. The command is idempotent — simply re-run it after every upgrade or configuration change.
npx harness init <your-config-name>npx harness doctorThen start your agent runtime from the project root — the skills appear as slash commands (/help lists them).
Four commands confirm everything is in place — each one names the next step if it fails.
npx harness version → AI Harness 2.0.1 (@aethon-x/[email protected]) npx harness license → License VALID — licensee, seats, and major version are shown npx harness doctor → "All checks passed." — every failed line names the command that fixes it npx harness init --dry-run → Preview of what a re-init would change — nothing is written
Minor and patch releases are included in your major version. Updating is a two-step:
npx harness upgrade # latest release within your licensed major npx harness init <config> # re-materialize the working structure afterwards
The Aethon-X Harness is a library of AI-assisted delivery workflows — from requirement intake to implementation, review, documentation, and deployment. Every phase is packaged as a versioned skill and runs as a slash command inside your own agent runtime.
No. The harness ships as text — skills, adapters, and a Node installer — and runs entirely inside the agent runtime you already use. There is no CloudRise server in the loop, no telemetry, and no phone-home. Even the license check runs offline.
Claude Code (recommended), OpenAI Codex CLI, Google Gemini CLI, local LLMs (Ollama / llama.cpp), and any hosted endpoint that speaks the OpenAI Chat Completions API — such as Scaleway, OVHcloud, IONOS, or STACKIT. Skills exist once and adapt at run time.
Yes. By default the configuration repository is cloned from GitHub, but any git URL works — your own GitHub organization, GitLab, Bitbucket, or an internal git server. The URL is only needed for the initial clone; afterwards the repository updates via a plain git pull.
The license is perpetual per major version; minor and patch updates are included. The license file carries an Ed25519 signature that the CLI verifies offline against a public key compiled into the package — nothing is transmitted, and no license server is contacted.
Find out in a no-obligation conversation how the harness accelerates your delivery process — including a live demo in your team's workflow.
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