jpeetz/agent-skills

hermes-bot-team-design

Use this skill when an agent needs to design a team of specialist Hermes bots from a project specification.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/jpeetz/agent-skills --skill hermes-bot-team-design

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

Hermes Bot Team Design

Design a team of specialized Hermes bots from a project specification. Each bot gets a SOUL.md with identity, behavior rules, handoff protocols, shared Memory section, and group chat integration. MCP servers (MeMex Zero RAG, HermesVault) are wired by default.

When to use

  • A new project needs a team of specialist bots
  • You are expanding an existing fleet
  • You are migrating an OpenClaw workflow to Hermes Bot Mode

The team design workflow

1. Read the project spec

Understand the full pipeline before deciding roles. Identify: pipeline phases, which need deep reasoning (expensive model) vs high-volume/mechanical (cheap model), outputs, and handoffs.

2. Decide team size and roles

Map each phase to a bot role:

  • Discovery / Research — high-volume, cheap model (DeepSeek V4 Flash)
  • Improvement / Creation — deep reasoning, expensive model (DeepSeek V4 Pro)
  • Validation / Publishing — mechanical, cheap model (DeepSeek V4 Flash)
  • Strategy / Direction — deep reasoning, expensive model (DeepSeek V4 Pro)
  • Content / Copy — creative, expensive model (DeepSeek V4 Pro)
  • UX / Design — creative, expensive model (DeepSeek V4 Pro)
  • Frontend / Backend — implementation, cheap model (DeepSeek V4 Flash)
  • Commerce / Marketplace — mechanical, cheap model (DeepSeek V4 Flash)

3. Create a group chat directory

bash
mkdir -p ~/workspace/MeMex-Zero-RAG/wiki/agentforge/group-chat/<project-name>/

Write a README.md with: protocol (file-based messaging), team roster (bot name, role, phase, model), pipeline flow, and communication rules.

4. For each bot, create the profile

~/.hermes/profiles/<name>/
├── SOUL.md      # Identity, Memory, behavior, handoffs
├── config.yaml  # model, provider, inherit_mcp_toolsets: true

SOUL.md sections: Frontmatter (name, description, role, teammates) → Identity → Memory (shared across all profiles — MeMex + HermesVault) → Group Chat → Browser verification → Behavior → Handoffs → Agent Inbox Protocol.

config.yaml:

yaml
model:
  default: <provider>/<model>
  provider: <provider>
platforms:
  telegram:
    enabled: false  # Team bots don't need Telegram

5. Wire MCP servers (mandatory)

Set inherit_mcp_toolsets: true to inherit MeMex Zero RAG (wikisearch, wikiread, wikiquery, wikiingest, wikilint) and HermesVault (readfile, searchfiles, listdirectory, readfileheader) from global config.

6. Write roster + drop initial message

Add the roster to the group chat README. Write a message from the director introducing the team, pipeline, and first task.

7. Verify

  • ls ~/.hermes/profiles/<name>/ — SOUL.md + config.yaml exist
  • hermes gateway list — gateway loads the new profile
  • Group chat has README.md + first message

Pitfalls

  • Do NOT create a bot without a SOUL.md
  • Do NOT skip the Memory section (shared brain between all bots)
  • Do NOT use expensive models for mechanical work — Scout (discovery) and Overseer (publishing) are cheap
  • Do NOT wire Telegram to team bots — they communicate via the group chat
  • Do NOT suggest UI buttons that don't exist — if the user says "there's no such button," find an alternative
  • Verify catalog files after rebase — conflict resolution can silently drop sibling rows

References

  • references/skill-foundry-example.md — full team design example (11 bots, Skill Foundry pipeline)
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