RuView is a WiFi sensing platform that uses disturbances in radio signals, captured by low-cost ESP32 sensors, to detect presence, movement, breathing, and heart rate without cameras or wearables. It is intended for spatial monitoring and smart-home integrations. The catalogue add-ons support workflows for operating and integrating RuView.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ruvnet/RuView --skill agentdb-learninggit clone --depth 1 https://github.com/ruvnet/RuViewWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ruvnet/ruview/agentdb-learning)<a href="https://agentmods.dev/skills/ruvnet/ruview/agentdb-learning"><img src="https://agentmods.dev/badge/skills/ruvnet/ruview/agentdb-learning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ruvnet/ruview/agentdb-learning"><img src="https://agentmods.dev/badge/skills/ruvnet/ruview/agentdb-learning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 16 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 28 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 31 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 34 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 37 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 44 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 58 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 61 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 124 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 152 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 179 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 204 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 485 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 488 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 491 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 494 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 538 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.02951 |
| Opus 5.5 | $0.00022 | $0.01180 |
| Sonnet 5.5 | $0.00011 | $0.00590 |
| Haiku 4.5 | $0.00006 | $0.00295 |
Grade A, and why
AgentDB Learning Plugins scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
8 near-identical copies found in the catalogue:
- AgentDB Learning Plugins — 100% identical, 18 lines differ
- AgentDB Learning Plugins — 100% identical, 0 lines differ
- AgentDB Learning Plugins — 100% identical, 0 lines differ
- AgentDB Learning Plugins — 100% identical, 0 lines differ
- AgentDB Learning Plugins — 100% identical, 0 lines differ
- AgentDB Learning Plugins — 100% identical, 18 lines differ
- AgentDB Learning Plugins — 100% identical, 0 lines differ
- AgentDB Learning Plugins — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 546 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentDB Learning Plugins
What This Skill Does
Provides access to 9 reinforcement learning algorithms via AgentDB's plugin system. Create, train, and deploy learning plugins for autonomous agents that improve through experience. Includes offline RL (Decision Transformer), value-based learning (Q-Learning), policy gradients (Actor-Critic), and advanced techniques.
Performance: Train models 10-100x faster with WASM-accelerated neural inference.
Prerequisites
- Node.js 18+
- AgentDB v1.0.7+ (via agentic-flow)
- Basic understanding of reinforcement learning (recommended)
Quick Start with CLI
Create Learning Plugin
# Interactive wizard
npx agentdb@latest create-plugin
# Use specific template
npx agentdb@latest create-plugin -t decision-transformer -n my-agent
# Preview without creating
npx agentdb@latest create-plugin -t q-learning --dry-run
# Custom output directory
npx agentdb@latest create-plugin -t actor-critic -o ./plugins
List Available Templates
# Show all plugin templates
npx agentdb@latest list-templates
# Available templates:
# - decision-transformer (sequence modeling RL - recommended)
# - q-learning (value-based learning)
# - sarsa (on-policy TD learning)
# - actor-critic (policy gradient with baseline)
# - curiosity-driven (exploration-based)
Manage Plugins
# List installed plugins
npx agentdb@latest list-plugins
# Get plugin information
npx agentdb@latest plugin-info my-agent
# Shows: algorithm, configuration, training status
Quick Start with API
import { createAgentDBAdapter } from 'agentic-flow/reasoningbank';
// Initialize with learning enabled
const adapter = await createAgentDBAdapter({
dbPath: '.agentdb/learning.db',
enableLearning: true, // Enable learning plugins
enableReasoning: true,
cacheSize: 1000,
});
// Store training experience
await adapter.insertPattern({
id: '',
type: 'experience',
domain: 'game-playing',
pattern_data: JSON.stringify({
embedding: await computeEmbedding('state-action-reward'),
pattern: {
state: [0.1, 0.2, 0.3],
action: 2,
reward: 1.0,
next_state: [0.15, 0.25, 0.35],
done: false
}
}),
confidence: 0.9,
usage_count: 1,
success_count: 1,
created_at: Date.now(),
last_used: Date.now(),
});
// Train learning model
const metrics = await adapter.train({
epochs: 50,
batchSize: 32,
});
console.log('Training Loss:', metrics.loss);
console.log('Duration:', metrics.duration, 'ms');
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 546 lines · 56 tokens per session scan A 5e52ac69d880
AgentDB Learning Plugins is a skill published in the GitHub repository ruvnet/RuView (98,659 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 2,951 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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