Hermes Skills Manager
6770bc9b9d
- Trading skills (OKX, dividend, lottery, quantitative) - Creative skills (ASCII art, diagrams, video) - Development skills (GitHub, debugging, TDD) - Research skills (arXiv, blog monitoring) - Productivity skills (email, documents, notes) - MCP integration skills - Custom user skills
92 lines
3.0 KiB
Markdown
92 lines
3.0 KiB
Markdown
# Deep Agents CLI Skills
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A curated pack of skills designed to empower your agent's **long-term memory** and **autonomy**. These skills act as middleware, letting your main session's agent decide when to delegate sub-tasks or manage its own context.
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---
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## Core Skill: `autosubagents` (Sub-Agent Orchestrator)
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Delegate complex, one-off tasks to a persistent sub-agent (often called the "Admin" or "Runner" session).
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**Trigger:** User sends a direct message or spawns a session.
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**Outcome:** Agent creates an isolated sub-agent session (`runtime="subagent"`) and sends it the task.
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### When to Use
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- When the current session gets too chatty and you need to "offload" work.
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- For tasks that need multiple tools or a dedicated context window.
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**Example Flow:**
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1. User sends: "Let's do that."
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2. Agent triggers: `deepagents autosubagent "That's the task."`
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3. Agent listens: Spawns sub-agent, waits for response.
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4. User gets: The sub-agent's finished summary.
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### Skills Packaged
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- **`context-compress`** (Autonomous Context Compression): Automatically summarize past messages when the session gets heavy.
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- **`session-history`** (Text-Based Fetch): Quickly grab the last N messages from another session.
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### How It Works
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```bash
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deepagents autosubagent --task "Summarize the last 5 chats"
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```
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---
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## Core Skill: `compact` (Context Compactor)
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A standalone tool that takes a "summary" session and injects its condensed message back into the parent session, effectively **compressing** the parent's history.
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**Trigger:** The parent session has received 3+ sub-agent responses.
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**Action:** Fetches the sub-agent's history, pulls out the "summary" payload, and pings it back.
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### How It Works
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1. **Parent** sends a task to **Sub-Agent**.
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2. **Sub-Agent** runs and uses `context-compress` to condense the chat.
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3. **Parent** receives the summary via a new message.
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### CLI Usage
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```bash
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deepagents compact --parent "main-session" --target "sub-session-name"
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```
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---
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## Setup Instructions
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### 1. Install the CLI
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```bash
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npm install -g deepagents
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```
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### 2. Configure in OpenClaw
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Point your OpenClaw `runtime` to a path where the CLI lives:
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```yaml
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# ~/.openclaw/env.d/
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deepagents:
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runtime: acp
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cwd: /path/to/deepagents-bin
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```
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### 3. Link the Skills Folder
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```bash
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ln -s ~/.openclaw/workspace/skills/deepagents ~/.deepagents/deep-organizer
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```
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---
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## Usage Patterns
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### Pattern A: "Set and Forget" (Best for one-off tasks)
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```bash
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deepagents autosubagent --task "Research this topic"
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```
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*The Agent will spawn a sub-agent, let it run its course, and return the results.*
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### Pattern B: "The Deep Work Loop"
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1. **Setup Phase:** Have the sub-agent pre-loaded with its own skills (`context-compress` + `session-history`).
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2. **Task Phase:** Spawn a new `autosubagent` instance for the day's main task.
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3. **Compression Phase:** Let the sub-agent do its thing. If the conversation gets long, have the sub-agent call `context-compress` automatically.
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---
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*Version: 1.0 — *Refined for OpenClaw's sub-agent ecosystem*.* |