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Skill Autogenesis

Name: Skill Autogenesis
Author: codeblackhole1024

作者 codeblackhole · GitHub ↗ · v1.3.2 · MIT-0

cross-platform ✓ 安全检测通过

120

总下载

当前安装

版本数

在 OpenClaw 中安装

/install skill-autogenesis

功能描述

Review completed work, summarize reusable procedures, identify recurring workflow patterns, and decide whether to create a skill, patch an existing skill, st...

安全使用建议

This skill is internally consistent and intentionally designed to convert recurring, verified workflows into skill files, but it will actively evaluate many completed tasks if loaded early in a session. Before installing or enabling it: (1) confirm you trust agents with the skill_manage tool and their ability to write to your skills directory (e.g., ~/.hermes/skills/); (2) decide whether you want autonomous creation/patching or prefer to require human approval — monitor outputs for the required internal classification template and recommended_action before any file writes; (3) ensure no secrets or sensitive information can be accidentally captured in generated skill content; (4) consider running it in a non-sensitive test session first so you can observe how often it proposes writes; (5) keep backups of your skills dir or review created files regularly and restrict agent tool permissions if you want tighter control.

功能分析

Type: OpenClaw Skill Name: skill-autogenesis Version: 1.3.2 The skill-autogenesis bundle is a meta-utility designed to help AI agents convert successful task workflows into reusable procedural memory (skills). It provides a structured framework for the agent to analyze its own actions, detect recurrence, and decide whether to create or patch skill files using tools like `skill_manage`. The bundle is characterized by extensive defensive logic, including a 'Decision Matrix' and 'Hard Stop Rules' (found in SKILL.md and references/hard-stop-rules.md) specifically designed to prevent the accidental creation of skills from sensitive data, user preferences, or one-off results. There is no evidence of malicious intent, data exfiltration, or unauthorized execution; the logic is entirely focused on organized knowledge management within the agent's designated environment.

能力标签

requires-sensitive-credentials

能力评估

✓ Purpose & Capability

The name and description match the actual behavior: distill workflows and, when appropriate, create/patch skills or store memory. It does not request unrelated binaries, environment variables, or network endpoints. All referenced capabilities (session_search, memory, skill_manage) are reasonable for the stated goal.

ℹ Instruction Scope

SKILL.md instructs the agent to inspect completed tasks, produce a classification template, estimate recurrence/stability, and only then call skill_manage(create|patch) or write memory. This stays within the skill's purpose. Note: the skill is designed to evaluate every 'meaningful' success by default, so if loaded early it will observe/consider many tasks — the gating (classification template and hard-stop rules) is explicit but users should be aware the agent will routinely evaluate workflows while the skill is active.

✓ Install Mechanism

Instruction-only skill with no install spec and no code files. No downloads, binaries, or package installs are required, which minimizes persistence and supply-chain risk.

✓ Credentials

The package declares no required environment variables, credentials, or config paths. The instructions reference tool APIs (skill_manage, session_search, memory) but do not require unrelated secrets or external credentials.

ℹ Persistence & Privilege

The skill can recommend or call skill_manage to create/patch skill files when the skill_manage tool is available — this is coherent with its purpose. It does not force always:true. Users should be aware that, if the agent has access to skill-management tools and file-write permissions (typical for agent-managed skills), the agent may autonomously write files into user skill directories (e.g., ~/.hermes/skills/) according to the documented gating rules.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install skill-autogenesis
安装完成后，直接呼叫该 Skill 的名称或使用 /skill-autogenesis 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.3.2

# Changelog ## 1.3.2 - Added hard stop rules that explicitly block invalid `skill_manage(create)` usage. - Tightened lifecycle rules so only `knowledge_type=procedure` may enter procedural skill actions. - Added `references/hard-stop-rules.md` with a fast test for valid skill candidates. - Updated the README to surface hard interception behavior. ## 1.3.1 - Added a mandatory internal classification template before any persistence action. - Added a checklist gate that must fully pass before create or patch is allowed. - Extended verification rules so create and patch require a completed decision record. - Updated the README to emphasize classification template first, file writes second. ## 1.3.0 - Added an explicit decision matrix to route outcomes to skill, memory, prompt, or no-op. - Added an output contract so agents classify the result before writing files. - Added a recurrence warning that repeated rules still do not qualify as skills without executable procedure. - Added `references/classification-examples.md` with concrete examples of what should and should not become a skill. ## 1.2.2 - Changed the default posture from implied creation to explicit classification first. - Added a hard gate that only executable reusable procedures may become skills. - Added routing guidance for non-skill outcomes such as preferences, policies, boundaries, and prompt-level governance. - Added a pitfall warning that rules are not skills unless they contain trigger, action, and verification. - Updated the bilingual README to reduce the common misread that this skill should create a new rule after every success. ## 1.2.1 - Refined positioning to emphasize verification-gated skill creation rather than unconditional autonomous writes. - Clarified that skill creation happens only when recurrence, stability, and environment policy permit it. - Tightened README wording to better communicate lifecycle controls and safety boundaries. - Kept local fallback reference behavior for GitHub sources. ## 1.2.0 - Added explicit source resolution policy: GitHub first, local fallback second, `[UNVERIFIED]` last. - Added local fallback reference files under `references/fallback/`. - Added `skill_manage`-style lifecycle handling for create, patch, edit, write_file, remove_file, and guarded delete. - Added reusable template file for generated skills. ## 1.1.0 - Added lifecycle-oriented behavior modeled after `skill_manage`. - Added support for supporting-file management and duplicate-skill avoidance. ## 1.0.0 - Initial release. - Added automatic workflow distillation, recurrence detection, and skill generation guidance.

v1.2.1

Clarified lifecycle safeguards, added release changelog, and emphasized verification-gated skill creation.

v1.2.0

Initial public release of skill-autogenesis with automatic skill distillation, skill_manage-style lifecycle handling, and local fallback references for GitHub sources.

元数据

Slug skill-autogenesis

版本 1.3.2

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 3

常见问题

Skill Autogenesis 是什么？

Review completed work, summarize reusable procedures, identify recurring workflow patterns, and decide whether to create a skill, patch an existing skill, st... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 120 次。

如何安装 Skill Autogenesis？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install skill-autogenesis」即可一键安装，无需额外配置。

Skill Autogenesis 是免费的吗？

是的，Skill Autogenesis 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

Skill Autogenesis 支持哪些平台？

Skill Autogenesis 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。

谁开发了 Skill Autogenesis？

由 codeblackhole（@codeblackhole1024）开发并维护，当前版本 v1.3.2。