Ruview Rvagent

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ruvnet

ruview-rvagent

Explore and prototype rvAgent + RVF integration for RuView agentic flows. Use when working on cross-cog coordination, operator-facing agents reading BFLD / pose / vitals events live, or persisting agent state alongside sensing data in the same RVF container.

Overview

Publisher	ruvnet
Repository	`RuView`
Skill name	`ruview-rvagent`
Stars	94.3K
Forks	12.5K
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by ruvnet on GitHub. Read the source before you install it.

Installation

Install the Ruview Rvagent AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/ruvnet/RuView.git /tmp/RuView
mkdir -p .claude/skills
cp -r /tmp/RuView/plugins/ruview/skills/ruview-rvagent .claude/skills/ruview-rvagent

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ruview Rvagent in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ruview Rvagent on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ruview Rvagent is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

RuView rvAgent + RVF integration

Surface area for wiring vendor/ruvector/crates/rvAgent/ into RuView so the existing sensing pipeline becomes the substrate an agentic flow can read, reason about, and respond to.

Quickstart — published MCP server (`@ruvnet/rvagent` v0.1.0)

Installing this plugin registers @ruvnet/rvagent as an MCP server. On activation, Claude Code spawns npx -y @ruvnet/rvagent and exposes its tools directly:

Tool	Purpose
`bfld_last_scan`	Most recent BFLD event from the sensing server
`bfld_subscribe`	Stream BFLD events for a window
`presence_now`	Current room-level presence state
`vitals_get_breathing`	Latest breathing-rate sample
`vitals_get_heart_rate`	Latest heart-rate sample
`vitals_get_all`	Composite vitals snapshot
`vitals_fetch`	Historical vitals window

Override the sensing-server URL via the RVAGENT_SENSING_URL env var (default http://localhost:3000). Source lives at tools/ruview-mcp/; ADR-124 captures the design.

Smoke-check the wiring: npm view @ruvnet/rvagent version should return 0.1.0 (or newer).

When to use this skill

"I want an agent that reacts to BFLD presence in the kitchen and pages the carer."
"I need cog-pose-estimation and cog-bfld to negotiate before publishing a synthesized event."
"Can the witness chain attest both the sensing event AND the agent decision in one RVF blob?"
"How do we keep rvAgent's tool outputs class-3 compliant when the source BFLD event is Restricted?"

Key surfaces

Surface	File	Notes
rvAgent core	`vendor/ruvector/crates/rvAgent/rvagent-core/src/agi_container.rs` (627 LOC)	RVF-compatible state container
rvAgent middleware	`vendor/ruvector/crates/rvAgent/rvagent-middleware/`	Witness, sanitizer, SONA, HNSW
Agent personas	`vendor/ruvector/crates/rvAgent/.ruv/agents/rvagent-{queen,coder,tester,security}.md`	Reference patterns
RVF container	`v2/crates/wifi-densepose-sensing-server/src/rvf_container.rs`	Add `SEG_AGENT_STATE`, `SEG_DECISION`
BFLD event	`v2/crates/wifi-densepose-bfld/src/event.rs`	`BfldEvent::to_json()` → `ToolOutput`
BFLD pipeline handle	`v2/crates/wifi-densepose-bfld/src/pipeline_handle.rs`	`BfldPipelineHandle::send`

Research dossier

Full integration analysis lives at docs/research/rvagent-rvf-integration/README.md.

Three shippable touchpoints, each independent:

RVF wire: two new segment types (SEG_AGENT_STATE = 0x08, SEG_DECISION = 0x09) let rvAgent sessions interleave with RuView sensing sessions in the same blob.
Tool surface: BfldEvent → ToolOutput shim turns BFLD events into agent context with no new IPC.
Cog subagents: cog-pose-estimation / cog-person-count / cog-ha-matter / cog-bfld register as rvAgent subagents under a queen-agent router.

Open questions

Workspace inclusion of vendor/ruvector/crates/rvAgent/ (path dep vs published crate)
Sync ↔ async adapter (BFLD Publish is sync, rvAgent backends are tokio)
Privacy-class composition (does rvAgent's sanitizer consume PrivacyClass?)
Soul Signature ↔ SoulMatchOracle bridge
Whether BfldPipelineHandle::send lands as a public MCP tool via rvagent-mcp

Next decision

ADR-124 (proposed) — "rvAgent + RVF integration for RuView agentic flows" — would capture segment assignments, cog-subagent contract, and the privacy-class composition rule. Land before scaffolding v2/crates/wifi-densepose-agent.

Frequently asked questions

What does the Ruview Rvagent AI skill do?

Why use Ruview Rvagent on TypingMind?

Because you install it once and use it with any model. Ruview Rvagent is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ruview Rvagent in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-rvagent. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ruview Rvagent?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ruview Rvagent?

As many as you like. As long as a model supports skills, you can use Ruview Rvagent with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ruview Rvagent AI skill free?

Yes. It is published on GitHub by ruvnet under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

RuView rvAgent + RVF integration

Quickstart — published MCP server (@ruvnet/rvagent v0.1.0)

When to use this skill

Key surfaces

Research dossier

Open questions

Next decision

Frequently asked questions

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Quickstart — published MCP server (`@ruvnet/rvagent` v0.1.0)