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Agent Operating System — Hermes is the command hub on Telegram.

Skill by percymcn

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/percymcn-agent-os

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About

Agent Operating System — Hermes is the command hub on Telegram. You talk to Hermes, Hermes orchestrates subagents (Felix/Claude Code), and results auto-save to memory. Built-in voice intent detection and cron job memory feedback.

Use cases: agent-building

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/agent-os

What's inside

Skill name
agent-os
Description
Agent Operating System — Hermes is the command hub on Telegram. You talk to Hermes, Hermes orchestrates subagents (Felix/Claude Code), and results auto-save to memory. Built-in voice intent detection and cron job memory feedback.
License
MIT
Instructions
98 lines in SKILL.md · view on GitHub

Agent Skills spec issues

  • files: referenced but missing: references/status-handoff-questions.md

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Agent OS — The Command Hub

## Architecture

```
You (Telegram voice/text)
    ↓
[1] Hermes receives — voice transcribed via faster-whisper / text direct
    ↓
[2] Intent detection — research | deploy | code | browse | cron | memory | question
    ↓
[3] Delegate or execute — delegate_task to subagents, or run cron jobs, or answer directly
    ↓
[4] Auto feedback — every result logs to ~/.hermes/agent-os/memory_log.jsonl
    ↓
[5] Dashboard updates — ~/.hermes/agent-os/dashboard.json always reflects latest state
```

## Core Scripts

### Feedback Loop
```
~/.hermes/scripts/agent-os-feedback.py
```
Usage:
```bash
python3 ~/.hermes/scripts/agent-os-feedback.py \
  --type delegate \
  --task "task description" \
  --result "what happened" \
  [--save-skill "lesson-name"]
```

### Voice Intent Detection
```
~/.hermes/scripts/voice-intent-pipeline.py
```
Usage:
```bash
echo "research the best AI voice agents" | python3 ~/.hermes/scripts/voice-intent-pipeline.py
```

Detects intents: research | deploy | code | browse | cron | question | memory | other

## Dashboard

- **`~/.hermes/agent-os/dashboard.json`** — JSON summary: total_recorded, by_type, last_10
- **`~/.hermes/agent-os/memory_log.jsonl`** — Full append-only log (auto-trimmed to last 200)
- **`~/.hermes/skills/agent-os-learned/*.md`** — Reusable lessons saved automatically

## User Interaction Signals

Purse issues commands with minimal words. The following signals mean **execute immediately** without confirmation or re-explanation:

| Signal | Meaning |
|--------|---------|
| "yes" | Go ahead with the plan you just described |
| "1 2" / "1 2 3" / numbered list | Execute those numbered steps in order |
| "?" | What's the current state? Report concisely |
| voice message | Transcribe → classify intent → execute (see Voice Intent Pipeline) |

When you receive one of these, do not ask for confirmation. Execute and report results.

### Status / Handoff Prompts Are Not Approval

Short questions like **"what is left"**, **"where are we"**, **"what now"**, **"what's pending"**, or **"what's left"** are status/handoff prompts. They mean: inspect current state first, then report pending items, blockers, and the next highest-leverage action.

Do **not** treat these as approval to create, run, or modify cron jobs/agents. Only execute a new side-effecting action when the user gives an explicit approval signal ("yes", "do it", numbered choice) or directly asks for that action.

See `references/status-handoff-questions.md` for the session note and recommended inspection sequence.

## When to Use This Skill

- User sends a voice message — transcribe → detect intent → delegate
- User says "remember this" — save to memory via the feedback script
- User replies "yes" or a number list to your plan — execute immediately
- Any task completes — call `agent-os-feedback.py --type cron --task "..." --result "..."`
- Checking system state — read `dashboard.json` for a quick overview

## Cron Job Integration

Every cron job script should call the feedback script on completion:
```python
subprocess.run([sys.executable, FEEDBACK_SCRIPT, "--type", "cron", "--task", "...", "--result", "..."])
```

## Intent Classifier Rules

| Intent | Triggers | Action |
|--------|----------|--------|
| research | "find out", "search", "research", "what is" | Web search + summarize |
| deploy | "deploy", "push live", "publish" | Deploy to Vercel/Gumroad/etc |
| code | "build", "fix", "debug", "create" | delegate_task to Claude Code |
| browse | "check site", "open url" | Browser automation via Felix |
| cron | "every day", "daily", "remind me" | Create cronjob |
| memory | "remember", "store" | Save to memory |
| question | "advice", "should I" | Direct answer from Hermes |

From percymcn/agent-cookbook, MIT.

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Last commit (this folder)
Jun 12, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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agent-os skill. Agent Mart. https://agentmart.dev/skills/percymcn-agent-os (last updated 2026-10-24)