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Built-in Skills

GolemBot ships with two built-in skills that are automatically copied into new assistant directories during golembot init or golembot onboard.

general — General Personal Assistant

A general-purpose skill that makes the agent a personal AI assistant.

Capabilities:

  • Answer questions, provide suggestions, brainstorm ideas
  • Read and write files: organize notes, generate reports, manage to-dos
  • Execute scripts and commands for task automation
  • Information retrieval and summarization

Persistent Memory:

The general skill establishes a notes.md convention for cross-session memory:

  • The agent reads notes.md at conversation start (if it exists)
  • Writes to it when the user asks to remember something, or after completing important tasks
  • Organized by topic: Preferences, Project Info, To-Do
  • Each entry tagged with [YYYY-MM-DD] date label
  • To-do items use Markdown checkbox format

Restrictions:

  • Only operates within the assistant directory
  • Does not modify golem.yaml, AGENTS.md, .golem/, or SKILL.md files

im-adapter — IM Response Guidelines

Optimizes the agent's responses for instant messaging platforms (Feishu, DingTalk, WeCom).

Response length:

  • Simple questions: 1–2 sentences, max 200 characters
  • Complex questions: sectioned, each section max 300 characters
  • Long content: key conclusion first, then offer detailed version

Formatting:

  • Avoid Markdown headers, code blocks, and tables (unless explicitly requested)
  • Use simple list markers (1. 2. 3. or -)
  • URLs directly, not Markdown link syntax

Group chat:

  • [User:xxx] prefix indicates group context
  • Address users by name
  • Extra concise to avoid flooding

Tone:

  • Conversational and natural
  • No overly formal greetings
  • Never start with "Sure, let me help you with..."

Template Skills

The onboard wizard offers 6 scenario templates, each with a specialized skill:

TemplateSkillKey behavior
customer-supportfaq-supportFAQ lookup from faq.md, escalation to unanswered.md
data-analystdata-analysisReads from data/, outputs to reports/, uses calc.py
code-reviewercode-review5-dimension review, severity tiers (Must/Should/Nice), outputs to reviews/
ops-assistantopsContent writing, scheduling via schedule.md, competitor tracking
meeting-notesmeetingStructured minutes, action items in action-items.md, archived to meetings/
researchresearchResearch reports with tables, sources in sources.md, archived to research/

Released under the MIT License.