# Train AgentDB Learning Plugins

Teams need practical guidance for reinforcement learning agents in AgentDB. This skill provides templates, training workflows, and evaluation patterns for learning plugins.

## Install

```bash
npx skillstore add dnyoussef/agentdb-learning-plugins
```

## Metadata

- Status: approved
- Slug: dnyoussef-agentdb-learning-plugins
- Skillstore revision: r1
- Version status: missing
- Tree hash: 2ac370685dbabf9483665383672bcfc650356de39cd8f7a6ce21d7f0e34e4116
- Author: DNYoussef
- GitHub username: DNYoussef
- License: MIT
- Repository: https://github.com/DNYoussef/ai-chrome-extension/tree/main/.claude/skills/agentdb-learning
- Ref: 0519034dad657fb1f7706e0550e962beeda73fdf
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, network
- Quality score: 77
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/dnyoussef-agentdb-learning-plugins
- Manifest: https://skillstore.pages.dev/api/skills/dnyoussef-agentdb-learning-plugins/manifest

## Capabilities

- Lists AgentDB CLI commands for creating and inspecting learning plugins.
- Explains nine reinforcement learning approaches supported by the guide.
- Shows TypeScript workflows for storing experiences and training models.
- Describes evaluation patterns using retrieved memories and confidence scores.
- Covers optimization patterns such as replay, batch training, and incremental learning.

## Use Cases

- Choose a Learning Template: Compare AgentDB templates and select an algorithm for a new learning plugin.
- Build an Experience Pipeline: Plan how an agent stores states, actions, rewards, and outcomes for later training.
- Improve Training Workflows: Use replay, batch training, and evaluation guidance to refine an existing plugin.

## Prompt Templates

### Create a Starter Plugin

```
Use this skill to help me choose an AgentDB learning plugin template for my task. Explain the recommended algorithm and first CLI steps.
```

### Plan Experience Storage

```
Help me design the experience fields for an AgentDB learning plugin. Include state, action, reward, next state, and completion status.
```

### Design a Training Workflow

```
Use this skill to outline a training workflow for my AgentDB plugin. Include batch size, epochs, validation, and evaluation checkpoints.
```

### Compare Advanced Strategies

```
Compare Decision Transformer, Actor-Critic, replay, and incremental learning for my agent. Recommend a strategy with tradeoffs and risks.
```

## Limitations

- It is a documentation skill and does not include executable plugin source files.
- It requires AgentDB and agentic-flow to be installed separately.
- Advanced sections assume reinforcement learning and TypeScript knowledge.
- It does not automatically verify model quality, data safety, or deployment readiness.

## Best Practices

- Start with the simplest algorithm that matches the action space and safety requirements.
- Store complete experience records so training and evaluation can use consistent signals.
- Evaluate learned decisions against held-out scenarios before using them in production agents.

## Anti Patterns

- Do not choose advanced algorithms before defining rewards and success criteria.
- Do not train only on successful episodes if failures are important for safety.
- Do not treat confidence scores as production guarantees without separate validation.

## Security Audit

- Audited at: 2026-07-09T11:42:04.721\+00:00
- Summary: Static analysis flagged Markdown backticks, documentation links, a relative SQLite example path, and one ordinary use-case bullet. Review found no prompt injection, hidden execution, credential access, or data exfiltration intent in SKILL.md.

## Stats

- Views: 252
- Downloads: 5
- Favorites: 0
- Popularity score: 0