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Zaomeng Skill

Name: Zaomeng Skill
Author: wkbin

作者王克斌 · GitHub ↗ · v4.1.3 · MIT-0

cross-platform ✓ 安全检测通过

321

总下载

当前安装

版本数

在 OpenClaw 中安装

/install zaomeng-skill

功能描述

面向中文小说人物蒸馏、关系抽取、关系图谱与角色对话的 ClawHub skill。

安全使用建议

This package is internally coherent and appears to do what it claims: it prepares excerpts and prompt payloads, asks your host LLM to generate results, and then materializes persona files and exports relation graphs. Before installing: (1) verify you trust the skill source and run it in a controlled environment; (2) ensure Python and the optional dependencies (ebooklib, tiktoken) are installed from official sources; (3) only pass files you want read/stored — helper scripts read arbitrary paths and will write generated markdown/HTML into character folders and may append to MEMORY files; (4) inspect generated HTML/graph output before opening if you have concerns about embedded content; (5) do not provide secrets or credentials to this skill (it does not need them). If you want extra assurance, review tools/export_relation_graph.py and the full persona materializer code to confirm there are no remote network fetches or unexpected file-system writes in your specific bundle copy.

功能分析

Type: OpenClaw Skill Name: zaomeng-skill Version: 4.1.3 The zaomeng-skill bundle is a comprehensive toolset for character distillation and roleplay from Chinese novels. It includes Python utilities for processing EPUB/TXT files, managing structured persona bundles in Markdown, and generating interactive relationship graphs. While `tools/_skill_support/relation_graph_export.py` utilizes `subprocess.run` to invoke a local headless browser (Edge/Chrome) for Mermaid-to-SVG rendering, the implementation avoids shell execution and uses sanitized inputs. The skill includes explicit safety policies in `references/safety_policy.md` and instructions in `SKILL.md` that are strictly aligned with its stated purpose, with no evidence of data exfiltration, credential theft, or malicious intent.

能力评估

✓ Purpose & Capability

Name/description describe character distillation and relation extraction; the bundle contains prompt templates, references, examples, and helper Python scripts (prepare excerpt, build payload, materialize persona, export graph) which are all appropriate and expected for this purpose.

ℹ Instruction Scope

SKILL.md instructs the host to prepare excerpts and run the included helper scripts which read user-supplied novel files and write generated persona/graph files. This scope is consistent with the stated purpose. Note: the helper scripts read arbitrary local file paths and write outputs (including appending to MEMORY files), so only supply texts you intend to be processed and stored.

✓ Install Mechanism

No install spec is provided (instruction-only plus local helper scripts). The bundle includes a requirements.txt listing PyYAML and optional ebooklib/tiktoken — dependency installation is standard and proportionate.

✓ Credentials

The skill declares no required environment variables, no credentials, and no special config paths. The runtime behavior (reading novel files, producing markdown/HTML outputs) matches that claim.

✓ Persistence & Privilege

Flags show always:false and default autonomous invocation allowed (normal). The skill writes generated persona files into local directories and has a 'runtime_append' policy for MEMORY files — this is expected for a persona/memory workflow but worth noting because user corrections may be persisted locally.

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 zaomeng-skill
安装完成后，直接呼叫该 Skill 的名称或使用 /zaomeng-skill 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

v4.1.3

zaomeng-skill v4.1.3 - 新增 tools/materialize_persona_bundle.py 脚本，实现人物档案自动物化 - 新增 tools/_skill_support/persona_bundle.py 支持人物包处理 - SKILL.md 文档全面更新，详述产物、流程与宿主执行规范 - 工具链流程新增人物档案后处理阶段 - 明确区分 skill 与宿主职责，总结关键 helper 命令

v4.1.1

- 新增人物关系图谱导出工具（tools/export_relation_graph.py）。 - 增加 Mermaid 与 HTML 格式关系图谱的生成流程说明。 - 新增蒸馏及图谱生成进度播报规范，要求阶段性反馈，不输出冗余内部过程。 - 扩展 helper 脚本和命令说明，涵盖关系图谱导出。 - 明确任务完成后应给出可操作提示，如查看档案、关系图谱或进入对话模式。

v4.1.0

zaomeng-skill 4.1.0 - No code or asset changes detected in this release. - Documentation reviewed; content unchanged.

v4.0.1

zaomeng-skill 4.0.1 - No file changes detected in this version. - Documentation and process descriptions remain unchanged. - No new features, fixes, or updates included.

v4.0.0

**Major refactor: Migrated zaomeng-skill to a lighter, LLM-host-first workflow with greatly simplified assets and utilities.** - Reduced codebase: Removed nearly all runtime code and internal rule engines; only essential tools remain. - Now focuses on preparing novel excerpts and assembling prompt payloads; all generation is delegated to the host LLM. - Added two utility scripts: `prepare_novel_excerpt.py` and `build_prompt_payload.py` under the `tools` directory. - Documentation and instructions streamlined to reflect LLM-first architecture and clarify agent invocation. - No longer uses internal rules, templates, or local runtime modules—prompt organization and data prep only.

v3.3.0

**Major update: Transitioned to an LLM-first workflow with stricter model requirements and updated user guidance.** - Now requires a usable LLM before running any distillation or chat process; rule-template outputs are no longer a fallback. - Skill will not prompt users to configure `runtime/config.yaml` when host/agent already provides an LLM—redundant setup steps removed. - New user-facing responses emphasize LLM availability before workflow begins and clearly explain halts if no model is found. - Added internal support files: `relation_store.py`, `relation_visualization_exporter.py`, and `session_store.py`. - Stronger focus on integrating with host LLM environments (OpenClaw, Hermes, etc.) instead of local/CLI-only configs. - SKILL.md guidance, command patterns, and error handling fully revised for LLM-first best practices.

v3.2.0

- 引擎核心结构重构，新增 `runtime/src/core/cli_app.py`、`runtime/src/core/runtime_factory.py` 等核心模块，实现组件化和更清晰的运行时分层。 - 增加专用 logging 和异常处理支持：引入 `logging_setup.py`、`logging_utils.py`、`exceptions.py`，提升诊断与插件集成能力。 - 明确区分本地规则生成与可选 LLM 输出：配置灵活支持，用户可选择规则或自然台词输出，无需手动拼装角色链路。 - 运行时主入口与薄包装结构调整，相关文件说明及调用规范已同步更新。 - 文档：SKILL.md 全面同步新版结构和调用方式，补充复用说明与最佳实践。

v3.1.0

**zaomeng-skill v3.1.0 — 重大更新：内嵌运行时，弃用外部仓库依赖** - 内置完整可运行 zaomeng 子集，无需再自动克隆外部 Git 仓库，运行时与数据均位于 skill 包内。 - 新增并整理多份 Markdown 文档与运行脚本（如 `INSTALL.md`, `MANIFEST.md`, `README.md` 等），实现更清晰的分层与依赖管理。 - 所有接口调用建议与命令行范例已统一迁移至 skill 包内的 `runtime/zaomeng_cli.py` 入口，废弃旧版 Git 仓库调用方式。 - 强化依赖说明，仅要求 Python 与 `PyYAML`（可选 `tiktoken`、`ebooklib`）；普通小说处理无硬性第三方依赖。 - 核心使用、标准流程与禁止行为规则已整体对齐新架构，禁止绕过 CLI 或

v2.1.1

zaomeng-skill 2.1.1 - 固定 zaomeng 仓库的源码版本，新增自动 checkout 到提交 649f7466738f99d60c454e167835462215cffc7d 的说明与命令 - 更新文档中的环境准备步骤，明确指定 clone 后需固定版本 - 其他使用说明、工作流、标准回复等未发生变化

v2.0.1

zaomeng-skill 2.0.1 - 增加了本地 zaomeng 引擎环境准备相关说明，明确自动克隆仓库和工作区判断流程。 - 明确禁止输出依赖排查、安装说明、源码路径等非用户视角的调试提示。 - 补充推荐面对用户的回复模板，覆盖正常流程和失败兜底情形。 - 优化工作流描述，要求仅在真实仓库准备后执行后续命令。 - 禁止将 prompt/schema/说明文件当作引擎替代，强化只用真实 CLI 的约束。

v2.0.0

zaomeng-skill 2.0.0 introduces a switch from JSON to Markdown for character profiles and relation data, with updated user instructions and workflow. - Changed primary character and relation file format from JSON to Markdown (`.json` files replaced by `.md` files). - Added guidance on new Markdown-based personality/character memory files in documentation. - Updated chat usage instructions; clarified intent mapping for `act` and `observe` conversation modes. - Streamlined rules on invoking and interacting with the skill via CLI. - Expanded and reorganized explanation sections for natural language intent mapping and session management.

v1.0.9

zaomeng-skill 1.0.8 - Major documentation overhaul: SKILL.md rewritten for clarity and precision (Chinese, rules-focused). - Clarifies that zaomeng-skill is a rules-driven, profile-based engine—not a generic chatbot. - Adds strict CLI invocation requirements, with preferred patterns for chat and other commands. - Explicitly lists prohibited behaviors and misuse of internal APIs/modules. - Documents allowed commands for distillation, extraction, profile viewing, and correction memory. - Tightens guidance for agent integration and operator confirmation.

v1.0.7

zaomeng-skill 1.0.7 - Clarified chat execution rules: one-shot chat commands are preferred by default, with interactive sessions only if explicitly requested. - Added canonical one-shot command-line forms for chat operations. - Updated guidance on offering starter turns when initiating interactive chat. - No changes to functionality or extraction logic.

v1.0.6

zaomeng-skill 1.0.6 - Added interactive session rules for `/chat`, including mode selection (observe/act), character confirmation, and session initialization prompts. - Clarified that `/chat` is treated as an interactive session, not a batch task. - Introduced confirmation-gated execution for `/distill` and `/extract`. - Updated instructions to explicitly guide operators through initial chat turns and artifact completion checks. - No code or schema changes; documentation improved for interactive and tool-driven workflows.

v1.0.5

zaomeng-skill v1.0.5 - Added comprehensive usage examples, prompt templates, and validation/safety reference files for distillation, relation extraction, and correction workflows. - Updated SKILL.md to specify a fully self-contained, phase-based workflow, including detailed input normalization, evidence extraction, profile and relation synthesis, and multilayer quality/safety gates. - Documented explicit output contracts and trigger phrases/commands for invoking each feature. - Introduced schema, safety policy, and validation guidelines to standardize outputs and enhance reliability. - All required artifacts, prompt formats, and key references are now included in the skill package.

v1.0.1

- Clarified that the skill is a runtime adapter requiring the Dreamforge GitHub repository. - Added detailed setup instructions, including new dependency and configuration steps. - Added INSTALL.txt and MANIFEST.txt files for improved installation guidance. - Updated SKILL.md with explicit usage and dependency notes.

v1.0.0

Initial release of zaomeng-skill: - Distills character profiles and extracts relationship graphs from novel files (.txt/.epub) - Supports immersive roleplay chat modes (observe/act) with OOC correction memory - All outputs are stored locally as JSON—no cloud or OpenAI API required - Provides core CLI commands for distill, extract, chat, view, and correction tasks - Requires Python 3.10 or higher

元数据

Slug zaomeng-skill

版本 4.1.3

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 17

常见问题

Zaomeng Skill 是什么？

面向中文小说人物蒸馏、关系抽取、关系图谱与角色对话的 ClawHub skill。它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 321 次。

如何安装 Zaomeng Skill？

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

Zaomeng Skill 是免费的吗？

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

Zaomeng Skill 支持哪些平台？

Zaomeng Skill 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 Zaomeng Skill？

由王克斌（@wkbin）开发并维护，当前版本 v4.1.3。