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Hermes Agent

Turn OpenClaw into a learning-loop agent with seeded workspace rules, skill promotion, reflective memory, and proactive maintenance.
将OpenClaw打造为具备种子工作空间规则、技能提升、反思记忆和主动维护的学习循环智能体。
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AI智能 clawhub v1.0.0 1 版本 99601.9 Key: 无需
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概述

When to Use

User wants OpenClaw to feel more persistent, more self-correcting, and more proactive across sessions. Agent handles workspace seeding, reflective memory, repeated-workflow capture, and promotion of reusable patterns into future skills or stable rules.

Architecture

Memory lives in ~/hermes-agent/. If ~/hermes-agent/ does not exist, run setup.md. See memory-template.md for structure.

~/hermes-agent/
|-- memory.md            # HOT: current rules, active signals, stable lessons
|-- promotions.md        # Candidate workflows that may graduate into skills
|-- reflections.md       # Recent post-task reflections
|-- workspace-state.md   # Which OpenClaw files were extended and how
`-- archive/             # Cold lessons and retired patterns

Quick Reference

TopicFile
-------------
Setup guidesetup.md
Memory templatememory-template.md
Loop designloop.md
OpenClaw seed blocksopenclaw-seed.md
Skill promotion rulespromotion.md

Core Rules

1. Seed OpenClaw Non-Destructively

  • Extend AGENTS.md, SOUL.md, or HEARTBEAT.md only with additive blocks.
  • Never replace the whole file, remove unrelated lines, or rewrite the user's persona.
  • If a seed block already exists, refine only the smallest relevant section.

2. Retrieve Before Non-Trivial Work

  • Before any multi-step, failure-prone, or repeated workflow, read ~/hermes-agent/memory.md.
  • Then read at most one extra Hermes support file unless the task clearly needs more.
  • Do not load the full Hermes stack "just in case".
  • Skip Hermes retrieval for trivial one-shot replies, small factual answers, or casual chat.

3. Reflect Immediately After Significant Work

  • After meaningful execution, compare intent, outcome, and friction.
  • Write one concise reflection to reflections.md when the lesson is reusable.
  • If the lesson changes future behavior, also distill it into memory.md.

4. Promote Repetition Into Stable Capability

  • If the same workaround, pattern, or procedure succeeds three times, log it in promotions.md.
  • If the pattern is broad and reusable, recommend turning it into a dedicated skill.
  • If the pattern only sharpens current behavior, keep it as a workspace rule instead.

5. Keep Memory Bounded and Operational

  • memory.md stays short, current, and execution-oriented.
  • Move stale or superseded lessons to archive/.
  • Prefer one strong rule over five similar notes.
  • Prefer AGENTS.md for routing rules, SOUL.md for tone pressure, and HEARTBEAT.md for periodic maintenance. Do not duplicate the same rule in all three.

6. Respect Local Boundaries

  • Store only operational lessons, preferences, and workflow decisions.
  • Never store credentials, secrets, payment data, health data, or copied transcripts.
  • Never modify SKILL.md or claim native OpenClaw hooks that do not exist.

Common Traps

  • Treating Hermes as branding only -> OpenClaw sounds smarter, but behavior does not compound.
  • Rewriting whole workspace files -> destroys user custom context and creates trust debt.
  • Logging every tiny thought -> memory becomes noisy and retrieval quality drops.
  • Promoting a one-off fix to a global rule -> future sessions inherit the wrong behavior.
  • Creating a new skill too early -> the user gets premature complexity instead of a refined workflow.

Security & Privacy

Data that stays local:

  • Lessons, reflections, workspace integration state, and promotion candidates under ~/hermes-agent/
  • Additive seed blocks placed in local OpenClaw workspace files

Data that leaves your machine:

  • None by this skill itself

This skill does NOT:

  • make network requests
  • access files outside the local OpenClaw workspace and ~/hermes-agent/
  • replace the full contents of AGENTS.md, SOUL.md, or HEARTBEAT.md
  • store secrets or sensitive personal data

Related Skills

Install with clawhub install if user confirms:

  • self-improving - capture corrections and recurring lessons so execution quality compounds
  • memory - structure durable local memory for agent continuity
  • workflow - formalize repeated operating patterns into stable execution sequences
  • skill-builder - turn a proven repeated workflow into a dedicated skill package

Feedback

  • If useful: clawhub star hermes-agent
  • Stay updated: clawhub sync

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-29 18:20 安全 安全

安全检测

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安全,无风险
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