Agent skill

Im Wiki Extractor

by cafe3310 in cafe3310/public-agent-skills

将超长群聊日志转化为结构化知识图谱。采用滑动窗口增量提取,规避上下文限制,并确保实体与关系的沉淀与溯源. An agent skill from cafe3310/public-agent-skills.

Apache-2.0Auto-check passed

Install Im Wiki Extractor

skills CLI
$ npx skills add cafe3310/public-agent-skills --skill im-wiki-extractor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install cafe3310/public-agent-skills im-wiki-extractor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/cafe3310/public-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills_parked/im-wiki-extractor .claude/skills/im-wiki-extractor && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
im-wiki-extractor
GitHub stars
255
Token cost
~669 tokens
SKILL.md length
205 words
Files
6 (incl. scripts)
Skills in repo
29
Repo updated
First seen
Licence
Apache-2.0

At a glance

将超长群聊日志转化为结构化知识图谱。采用滑动窗口增量提取,规避上下文限制,并确保实体与关系的沉淀与溯源. An agent skill from cafe3310/public-agent-skills.

  • Works in 5 steps: 概述 (Overview) → 提取定义 (Schema) → 工作流阶段 (Workflow Phases) → …
  • SKILL.md covers 1. 概述 (Overview), 2. 提取定义 (Schema), 3. 工作流阶段 (Workflow Phases) and 4. 执行原则 (Execution Principles), plus 1 more section
  • Runs Python scripts from its folder; calls python

What it does

Im Wiki Extractor is an agent skill from cafe3310/public-agent-skills. 将超长群聊日志转化为结构化知识图谱。采用滑动窗口增量提取,规避上下文限制,并确保实体与关系的沉淀与溯源

Its SKILL.md is about 670 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts (for example `memories-off-declare.md`, `scripts/generate_prompt.py` and `scripts/setup_workspace.py`).

The repository describes itself as: personal agent skills for better QoL. The licence is Apache-2.0.

Example prompts

  • “/im-wiki-extractor”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. 概述 (Overview)
  2. 提取定义 (Schema)
  3. 工作流阶段 (Workflow Phases)
  4. 执行原则 (Execution Principles)
  5. 资源清单 (Resources)

What it can do on your machine

Read from SKILL.md and the folder at commit 6c45501. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Im Wiki Extractor loads about 669 tokens when it runs. Until then it costs about 17 tokens; SKILL.md has 205 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~17
When it runs · the whole SKILL.md, loaded when a task matches
~669

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from cafe3310/public-agent-skills at commit 6c45501, republished under its Apache-2.0 licence (© cafe3310). 205 words, ~669 tokens.

Download SKILL.mdSave it as .claude/skills/im-wiki-extractor/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
im-wiki-extractor
description
将超长群聊日志转化为结构化知识图谱。采用滑动窗口增量提取,规避上下文限制,并确保实体与关系的沉淀与溯源
license
Apache-2.0
author
github/cafe3310
depends_on_skill
github/cafe3310/agent-skill-memories-off -> memories-off
depends_on_binary
python3

Agent Skill: im-wiki-extractor (群聊知识图谱提取器)

1. 概述 (Overview)

本技能旨在将非结构化的聊天记录(如群聊历史)转化为存储在 memories-off Agent Skill 生成的仓库中的结构化知识图谱。 它强调「逐渐增量」的处理方式,通过 100 行一个的「滑动窗口」来处理超长日志,从而规避模型上下文限制。 该技能通过动态注入工具的 help 信息来确保子代理生成 100% 正确的 CLI 指令。

外部依赖与规范说明

本 Skill 依赖 memories-off 库进行实体管理与长期记忆。在执行任何任务前,您必须先查阅并完整遵循当前目录下的 memories-off-declare.md 声明文档,以获取其定义的实体类型规范及封装的子过程操作细节。

2. 提取定义 (Schema)

提取任务应遵循用户给出的实体和关系规范。 在 templates/meta.md 中包含了一个示例定义,定义了实体的类型(Member, Opinion, Info 等)及其关系谓语(Propose, Discuss 等)。 用户可以根据实际需求进行调整。

3. 工作流阶段 (Workflow Phases)

第一阶段:准备与访谈
  1. 确认范围: 询问语料位置及目标知识库目录。
  2. Schema 确认: 引导用户确认 templates/meta.md。
  3. 目标定义: 确认 templates/prompt_template.md。
第二阶段:空间初始化
  1. 初始化 memories-off 仓库: 在用户指定的地方创建知识目录并执行 memocli init。
  2. 配置元数据: 用 cp 命令将 templates/meta.md 的内容写入知识库的 meta.md;或根据用户之前的输入动态生成 meta.md。
  3. 复制语料: 在 memocli init 创建的知识库中创建 chat_res 子目录,用于存储规范化后的原始语料;然后将原始日志复制到 chat_res,按顺序重命名为 YYYY-MM-DD_NNN_orig_name.md。
  4. 任务分解与状态追踪: 运行 python scripts/setup_workspace.py path_to_chat_res TASK_YYYY-MM-DD.md。该脚本会扫描语料并生成带有行号分片(100行)和前序上下文(50行)的 TASK 文件。
第三阶段:增量提取循环 (断点续传)

针对 TASK 文件中定义的每个未完成分片([ ]):

  1. 自动定位: 启动任务时,直接定位到 TASK 文件中第一个 [ ] 状态的分片开始处理。
  2. 生成提示词: 运行 python scripts/generate_prompt.py ...。该脚本现在会动态注入支持「组合操作」的 memocli 语法(如在追加内容的同时建立关系)。
  3. 执行提取子任务 (原子化操作):
    • 组合指令优先: 优先使用 append-update --add-rel-out 等组合指令,减少工具调用次数。
    • 路径自动探测: 默认在知识库根目录执行,无需显式传入 --path。
    • 失败处理: 若执行中断,直接在下一次尝试时重新处理该分片。
  4. 记录与提交:
    • 检查 TASK 文件,确认分片状态已更新为 [x]。
    • 标准化提交: 执行 memocli commit -r "processed chunk [ID]"。该命令会自动触发全库审计并生成标准的 Git 提交信息。
  5. 检查并继续: 进入下一个分片。

4. 执行原则 (Execution Principles)

  • 命名规范 (Identity): 实体名即文件名。严禁添加类型前缀。
  • 组合语义 (Combined Ops): 充分利用 memocli 的 --add-rel-out/in 参数。在 create-entity 或 append-update 时同步完成关系建模,提升提取效率。
  • 动态语法核验: generate_prompt.py 会实时调用 memocli --help 以确保子代理使用的语法与当前环境安装的版本 100% 匹配。
  • 最小化探测:
    • 识别到实体后直接 create-entity,通过 || true 忽略已存在错误。
    • 严禁冗余的 ls 或全局 search。
  • 溯源强制: 所有的 append-update 必须包含 filename:line_range。

5. 资源清单 (Resources)

脚本 (Scripts)
  • scripts/setup_workspace.py: 初始化分片任务清单。
  • scripts/generate_prompt.py: 动态组装包含权威 CLI 语法的子代理提示词。
模板 (Templates)
  • templates/prompt_template.md: 核心任务模板,包含元数据和工具操作占位符。
  • templates/meta.md: 图谱本体定义模板。

© cafe3310, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts) in skills_parked/im-wiki-extractor of cafe3310/public-agent-skills.

  • SKILL.md
  • memories-off-declare.md
  • scripts/generate_prompt.py
  • scripts/setup_workspace.py
  • templates/meta.md
  • templates/prompt_template.md

Open the folder on GitHubat commit 6c45501

Compare with similar skills

Im Wiki Extractor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Im Wiki Extractor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Im Wiki Extractor this skillcafe3310/public-agent-skills255—~669Automated safety check: PassApache-2.0
Wiki Maintaineropenclaw/openclaw392k1 repos~462Automated safety check: PassMIT
LLM WikiYeachan-Heo/oh-my-claudecode40k—~721Automated safety check: PassMIT
Wiki Querypaperclipai/paperclip99k—~682Automated safety check: PassMIT
Wiki Lintpaperclipai/paperclip99k—~878Automated safety check: PassMIT
Wiki Ingestpaperclipai/paperclip99k—~933Automated safety check: PassMIT

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Questions about Im Wiki Extractor

What does Im Wiki Extractor do?

将超长群聊日志转化为结构化知识图谱。采用滑动窗口增量提取,规避上下文限制,并确保实体与关系的沉淀与溯源. An agent skill from cafe3310/public-agent-skills. Im Wiki Extractor is an agent skill from cafe3310/public-agent-skills.

How do I install Im Wiki Extractor in Claude Code?

Run `npx skills add cafe3310/public-agent-skills --skill im-wiki-extractor -a claude-code`. Or copy the skill folder (skills_parked/im-wiki-extractor in cafe3310/public-agent-skills) into .claude/skills/im-wiki-extractor in your project. Claude Code loads it when a task matches its description.

How do I install Im Wiki Extractor in Codex?

Run `npx skills add cafe3310/public-agent-skills --skill im-wiki-extractor -a codex`. Or copy the skill folder (skills_parked/im-wiki-extractor in cafe3310/public-agent-skills) into .agents/skills/im-wiki-extractor in your project. Codex loads it when a task matches its description.

Can I use Im Wiki Extractor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add cafe3310/public-agent-skills --skill im-wiki-extractor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/im-wiki-extractor, .gemini/skills/im-wiki-extractor, .github/skills/im-wiki-extractor and .opencode/skills/im-wiki-extractor in your project.

What does Im Wiki Extractor need to run?

Going by SKILL.md and its folder, Im Wiki Extractor needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Im Wiki Extractor access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Im Wiki Extractor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Im Wiki Extractor use?

Im Wiki Extractor is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Im Wiki Extractor use?

About 669 tokens (SKILL.md is roughly 2.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Im Wiki Extractor?

Skills that share tags, products or a category with Im Wiki Extractor: Wiki Maintainer (openclaw/openclaw, 392k stars), LLM Wiki (Yeachan-Heo/oh-my-claudecode, 40k stars), Wiki Query (paperclipai/paperclip, 99k stars) and Wiki Lint (paperclipai/paperclip, 99k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Im Wiki Extractor?

cafe3310 (a GitHub user) maintains it in cafe3310/public-agent-skills, which has 255 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on June 26, 2026.

Source: cafe3310/public-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.