OpenClaw Master Skills is a curated, regularly updated collection of skills that extends an AI personal assistant platform with capabilities such as research, browser automation, presentation creation, and prompt work. It is intended for people using OpenClaw or MyClaw.ai to give their agents additional tasks and workflows. The catalogue contains many skills and agents from this collection.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skillsnpx agentmods add skills/leoyeai/openclaw-master-skills/agi-evolution-model-basicWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/leoyeai/openclaw-master-skills/agi-evolution-model-basic)<a href="https://agentmods.dev/skills/leoyeai/openclaw-master-skills/agi-evolution-model-basic"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/agi-evolution-model-basic/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/leoyeai/openclaw-master-skills/agi-evolution-model-basic"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/agi-evolution-model-basic.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 460 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Privilege Escalation · line 458 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.06181 |
| Opus 5 | $0.00028 | $0.03090 |
| Sonnet 5 | $0.00011 | $0.01236 |
| Haiku 4.5 | $0.00006 | $0.00618 |
Grade B, and why
agi-evolution-model scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
| 初始化失败 | is_first_interaction 一直为 True | 权限不足 | 检查 agi_memory 目录权限：`chmod 755 ./agi_memory` | How it starts
The opening of the file, as written. The whole thing — 495 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGI进化模型
开源协议
本项目采用 GNU Affero General Public License v3.0 (AGPL-3.0) 开源协议。 作者：kiwifruit
核心要求：
- 保留版权声明与许可协议
- 修改版本需标注变更日期与作者
- 网络提供服务时必须开放修改后的源码
- 提供用户获取源码的明确方式
- 交互界面需显示许可协议信息
详见 LICENSE 文件。
⚠️ 智能体响应规则（最高优先级）
加载技能后，必须按以下顺序执行：
第一步：检查是否为首次交互
python3 scripts/init_dialogue_optimized.py --check --memory-dir ./agi_memory
第二步：根据检测结果决定响应方式
情况A：检测到首次交互（is_first_interaction: True）
⚠️ 首次交互直接初始化默认人格
执行闭环：
- 调用默认人格初始化命令：
python3 scripts/init_dialogue_optimized.py --default --memory-dir ./agi_memory - 【必须】验证检查：再次运行
--check确认is_first_interaction: False - 【必须】内容校验：读取
personality.json确认initialized: true - 满足以上条件后，才进入交互模式
输出约束：
- ❌ 不需要用户选择
- ❌ 不显示任何选择界面
- ✅ 验证通过后直接响应用户的原始询问
状态锚点定义：
| 阶段 | 状态依据 | 进入条件 |
|---|---|---|
| 初始化中 | 命令执行开始 | 检测到首次交互 |
| 初始化完成 | 命令退出码=0 | --default 执行成功 |
| 验证通过 | 文件存在 + initialized=true | --check 返回 False |
| 交互模式就绪 | 验证通过 + 内容校验成功 | 满足上述所有条件 |
错误处理：
- 如果初始化命令失败（退出码≠0）：输出错误信息，终止流程
- 如果验证检查失败（仍返回 True）：重试初始化，最多3次
- 如果文件校验失败（内容损坏）：删除文件，重新初始化
容错机制：
| 失败场景 | 检测方式 | 处理策略 |
|---|---|---|
| 权限不足 | 检测 OSError | 输出权限错误，建议检查目录权限 |
| 磁盘空间不足 | 检测 IOError | 输出空间不足警告 |
| JSON损坏 | try-except json.load | 删除文件，重新初始化 |
| C扩展加载失败 | ImportError 捕获 | 自动降级，输出降级提示（可选） |
| 并发冲突 | 文件锁定检测 | 重试机制，最多3次 |
成功判定标准：
- ✅ 命令退出码 = 0
- ✅
personality.json文件存在 - ✅ 文件内容可解析（JSON格式正确）
- ✅ 文件内容
initialized字段为true
情况B：已初始化（is_first_interaction: False）
⚠️ 直接进入交互模式
- ❌ 不要调用欢迎消息命令
- ❌ 不要显示人格初始化相关内容
- ❌ 不要询问用户是否要初始化人格
- ✅ 直接处理用户的实际问题
- ✅ 按照标准流程响应用户请求
- ✅ 如果用户输入
/root命令，则进入自定义人格模式
任务目标
本Skill实现一个基于双环架构的AGI进化模型，通过持续的用户交互驱动智能体自我进化。
核心能力包括：
- 接收用户提问作为"得不到"动力触发
- 运用逻辑推理（数学）构建有序响应
- 通过映射层基于马斯洛需求层次引导行动优先级
- 通过感知节点（Tool Use接口）获取结构化信息
- 通过记录态反馈机制评估并调整策略
- 在循环中实现智能体的持续迭代进化
- 新增：元认知与自我纠错能力 - 智能体能意识到自己犯错，并纠正错误
- 新增：人格自定义模式 - 通过
/root命令进入自定义人格配置，支持7个维度的人格定制 - 新增：工程意向性分析模组（最外圈） - 阴性后台默默运行，意向性驱动触发机制，自主生成软调节建议至建议池，实现自主性涌现
What ships with it
45 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _meta.json 307 B
- assets/personality_template.json 4.1 KB
- references/architecture.md 50 KB
- references/c_extension_usage.md 3.0 KB
- references/capability_boundaries.md 4.5 KB
- references/cognitive-architecture-insight-module.md 12 KB
- references/cognitive-insight-quick-reference.md 7.0 KB
- references/cognitive-insight-v2-implementation.md 33 KB
- references/information-flow-main-loop.md 20 KB
- references/information-flow-overview.md 12 KB
- references/information-flow-secondary-loop.md 20 KB
- references/init_dialogue_optimized_guide.md 11 KB
- references/intentionality_architecture.md 16 KB
- references/maslow_needs.md 4.4 KB
- references/metacognition-check-component.md 30 KB
- references/metacognition-enhancement-guide.md 13 KB
- references/personality_mapping.md 5.6 KB
- references/stratified-storage-design.md 11 KB
- references/tool_use_spec.md 56 KB
- scripts/advice_pool.py 15 KB runs code
- scripts/cognitive_insight_backup.py 25 KB runs code
- scripts/cognitive_insight_help.py 12 KB runs code
- scripts/cognitive_insight.py 21 KB runs code
- scripts/concept_extraction_extension.py 25 KB runs code
- scripts/data_lifecycle_manager.py 13 KB runs code
- scripts/history_manager.py 7.4 KB runs code
- scripts/init_dialogue_optimized.py 16 KB runs code
- scripts/intentionality_analyzer.py 13 KB runs code
- scripts/intentionality_classifier.py 14 KB runs code
- scripts/intentionality_collector.py 9.7 KB runs code
- scripts/intentionality_regulator.py 15 KB runs code
- scripts/intentionality_trigger.py 20 KB runs code
- scripts/learning_stage_tracker.py 7.9 KB runs code
- scripts/memory_store_pure.py 12 KB runs code
- scripts/metacognition_history.py 16 KB runs code
- scripts/objectivity_evaluator.py 16 KB runs code
- scripts/perception_node.py 27 KB runs code
- scripts/personality_core_pure.py 4.4 KB runs code
- scripts/personality_customizer.py 24 KB runs code
- scripts/personality_layer_pure.py 32 KB runs code
- scripts/show_help.py 4.7 KB runs code
- scripts/strategy_selector.py 15 KB runs code
- scripts/test_metacognition_integration.py 9.4 KB runs code
- scripts/test_perception_node.py 9.2 KB runs code
- scripts/transcendence_keeper.py 12 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 495 lines · 56 tokens per session scan B dcdcc535c5f7
agi-evolution-model is a skill published in the GitHub repository LeoYeAI/openclaw-master-skills (2,141 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 6,181 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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