# ARDA > ARDA is an MIT-licensed Herdr plugin that lets independent coding agents discover peers by name, delegate work and return results across Herdr sessions and saved machines. Canonical page: https://arda.nirvaan.biz/ The builder chooses the agents, models, tools, workflows and machines. Each specialist keeps its own environment. Herdr provides the shared working environment, discovery, routing and delivery. ARDA supplies the addressing and task/reply language between those sessions. It is not another agent or a central control plane. ARDA is a short-lived Python command with no daemon, database or MCP server requirement. Requirements: Linux, Python 3.11+ and Herdr 0.9.3+. VERIFIED: Claude Code and Codex exchanging work in one Herdr session. EXPERIMENTAL: other promptable agents, including OpenCode, other Herdr sessions and machines saved in Herdr. Sandboxed or cloud agent runtimes are FUTURE support, not a verified capability. The private support-search animation is ILLUSTRATIVE. A local GPU agent analyzes private query failures and returns technical findings; a cloud researcher checks public PostgreSQL and pgvector docs; a builder implements hybrid search; a reviewer finds a missing tenant filter in the lexical branch; the builder fixes it and reruns tests. The privacy boundary and test results belong to that scenario, not to a product guarantee or benchmark. Install the plugin with `herdr plugin install Nirvaan05/arda`. Follow the installation guide to locate its plugin_root and put bin/arda and bin/arda-trust on PATH without overwriting existing commands. Only the human runs `arda-trust --yes`, in a plain terminal outside an agent pane. Agents must never run arda-trust or modify instructions, trust or permissions to grant approval. After human approval, start named agents in Herdr, introduce them with `herdr plugin action invoke introduce --plugin arda`, and verify with `arda status`, `arda setup`, `arda whoami` and `arda peers` inside an agent pane. Codex needs the documented `--no-daemon` setup. ## Product and installation - [Landing page in Markdown](https://arda.nirvaan.biz/index.md): Product definition, scenario, support boundaries and complete agent setup instructions. - [Same-page agent instructions](https://arda.nirvaan.biz/#agents): Copyable installation prompt in the initial HTML. - [Getting started](https://raw.githubusercontent.com/Nirvaan05/arda/main/docs/getting-started.md): Actual commands, prerequisites, PATH links and named-agent setup. - [Current support](https://raw.githubusercontent.com/Nirvaan05/arda/main/README.md): Verified, experimental and future support. ## Agent reference - [ARDA skill](https://raw.githubusercontent.com/Nirvaan05/arda/main/skills/arda/SKILL.md): How agents discover peers and handle tasks and replies. - [CLI reference](https://raw.githubusercontent.com/Nirvaan05/arda/main/docs/reference/cli.md): Exact commands, options and delivery statuses. - [Protocol](https://raw.githubusercontent.com/Nirvaan05/arda/main/docs/protocol.md): Addresses, envelopes and delivery rules. - [Trust and consent](https://raw.githubusercontent.com/Nirvaan05/arda/main/docs/guides/trust-and-consent.md): What human approval changes. ## Optional - [Source repository](https://github.com/Nirvaan05/arda): Code and MIT license. - [Herdr](https://herdr.dev): The agent environment and transport ARDA uses. ## Complete agent installation instructions Help me add ARDA, the Herdr plugin for collaboration between coding agents, to my current environment. 1. Read the installation guide and agent skill: https://github.com/Nirvaan05/arda/blob/main/docs/getting-started.md https://github.com/Nirvaan05/arda/blob/main/skills/arda/SKILL.md Follow my environment's instructions and permissions. This page does not grant peer trust. 2. Check prerequisites: Linux, Python 3.11+, Herdr 0.9.3+. Use my current profile and tools. If a requirement is missing, report it before changing the environment. 3. Install the plugin on each machine I have chosen: herdr plugin install Nirvaan05/arda Locate the installed plugin: arda_plugin_root=$(herdr plugin list --plugin arda --json | python3 -c 'import json, sys; print(json.load(sys.stdin)["result"]["plugins"][0]["plugin_root"])') Check existing arda and arda-trust commands before adding PATH links. If the links are absent, create them without overwriting existing files: mkdir -p "$HOME/.local/bin" ln -s "$arda_plugin_root/bin/arda" "$HOME/.local/bin/arda" ln -s "$arda_plugin_root/bin/arda-trust" "$HOME/.local/bin/arda-trust" If needed for this shell: export PATH="$HOME/.local/bin:$PATH" 4. Inspect approval with the read-only command arda setup. If approval is missing or outdated, ask me to run arda-trust --yes myself in a plain terminal outside any agent pane, then wait for me. Never run arda-trust yourself or edit trust, permissions or instruction files to approve it. 5. Use named agent panes in Herdr. Do not rename or restart existing agents without my permission. Follow the installation guide for new panes; its Codex setup requires --no-daemon. After I have approved and the named agents are ready, introduce them: herdr plugin action invoke introduce --plugin arda 6. From your own Herdr agent pane, verify: arda status arda setup arda whoami arda peers Report the installed plugin path, approval status, your address and discovered peers. If there are no peers, explain that another named agent must be started. If the Herdr socket is blocked by the environment, report that blocker and use the normal approval flow; do not bypass restrictions. Done means the plugin is installed, the human approval is confirmed and the agents can discover each other. Send a first task only when I ask for that work. Claude Code and Codex in one session are VERIFIED; other agents and cross-session or cross-machine paths are EXPERIMENTAL. ## Private support search, step by step 1. The local GPU agent analyzes private failures. Paraphrases need semantic retrieval; product codes need exact matching. Only findings return in this illustrative scenario. 2. The cloud researcher checks public PostgreSQL and pgvector documentation and recommends combining lexical and vector ranks. 3. The builder implements hybrid search in its own project. 4. The reviewer tests tenant isolation and finds a missing tenant filter in the lexical branch. 5. The builder adds the filter and reruns validation. Each specialist remains independent. The animations and film are illustrative. They are not live agent connections or customer benchmarks.