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History Insight

Organization
team-attention
history-insight

This skill should be used when user wants to access, capture, or reference Claude Code session history. Trigger when user says "capture session", "save session history", or references past/current conversation as a source - whether for saving, extracting, summarizing, or reviewing. This includes any mention of "what we discussed", "today's work", "session history", or when user treats the conversation itself as source material (e.g., "from our conversation").

Overview

Publisherteam-attention
Repositoryplugins-for-claude-natives
Skill namehistory-insight
Stars
827
Forks
106
Bundled files
2
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by team-attention on GitHub. Read the source before you install it.

Installation

Install the History Insight AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/team-attention/plugins-for-claude-natives/tree/main/plugins/session-wrap/skills/history-insight
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/team-attention/plugins-for-claude-natives.git /tmp/plugins-for-claude-natives
mkdir -p .claude/skills
cp -r /tmp/plugins-for-claude-natives/plugins/session-wrap/skills/history-insight .claude/skills/history-insight
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable History Insight in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads History Insight on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so History Insight is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

History Insight

Claude Code 세션 히스토리를 분석하고 인사이트를 추출합니다.

Data Location

~/.claude/projects/<encoded-cwd>/*.jsonl

Path Encoding: /Users/foo/project → -Users-foo-project

상세 파일 포맷: ${baseDir}/references/session-file-format.md

Execution Algorithm

Step 1: Ask Scope [MANDATORY]

스코프 결정:

  1. 명시된 경우 (AskUserQuestion 생략 가능):

    • "현재 프로젝트만" / "이 프로젝트" → current_project
    • "모든 세션" / "전체" → all_sessions

  2. 명시되지 않은 경우 - AskUserQuestion 호출:

    question: "세션 검색 범위를 선택하세요"
options:
  - "현재 프로젝트만" → ~/.claude/projects/<encoded-cwd>/*.jsonl
  - "모든 Claude Code 세션" → ~/.claude/projects/**/*.jsonl

Step 2: Find Session Files

bash
# Current project only
find ~/.claude/projects/<encoded-cwd> -name "*.jsonl" -type f

# All sessions (모든 프로젝트)
find ~/.claude/projects -name "*.jsonl" -type f

날짜 필터링: 파일의 mtime(수정시간) 확인 후 필터. OS별 stat 옵션 다름:

  • macOS: stat -f "%Sm" -t "%Y-%m-%d" <file>
  • Linux: stat -c "%y" <file>

Step 3: Process Sessions

Decision Tree
Session files found?
├─ No → Error: "No sessions found"
└─ Yes → How many files?
    ├─ 1-3 files → Direct Read + parse
    └─ 4+ files → Batch Extract Pipeline
1-3 Files

직접 Read로 JSONL 파싱. 파일이 크면(≥5000 tokens) extract-session.sh 사용:

bash
${baseDir}/scripts/extract-session.sh <session.jsonl>
4+ Files: Batch Extract Pipeline
  1. 캐시 디렉토리 생성 (/tmp/cc-cache/<analysis-name>/)
  2. 세션 목록 저장 (sessions.txt)
  3. jq로 메시지 일괄 추출 (user_messages.txt)
  4. 정리 및 필터링 (clean_messages.txt)
  5. Task(opus)로 종합 분석
파일이 너무 클 때: 병렬 배치 분석

clean_messages.txt가 너무 커서 Read 실패 시:

  1. 파일 분할:

    bash
    split -l 2000 clean_messages.txt /tmp/cc-cache/<name>/batch_

  2. 병렬 Task(opus) 호출:

    Task(subagent_type="general-purpose", model="opus", run_in_background=true)
prompt: "batch_XX 파일을 읽고 주제/패턴 요약해줘"

  3. 결과 병합: Task(opus)로 종합

Step 4: Report Results

markdown
## Session Capture Complete

- **Sessions:** N files processed
- **Messages:** X total, Y after filter

### Extracted Insights
[분석 결과]

Error Handling

ScenarioResponse
No session files found"No session files found for this project."
File too largeAuto-preprocess with extract-session.sh
jq not installed"Error: jq is required. Install with: brew install jq"
Task failed"Warning: Could not process [file]. Skipping."
0 relevant sessions"No sessions matched your criteria."

Security Notes

  • 출력에 전체 경로 노출 금지 (~ prefix 사용)

Related Resources

  • ${baseDir}/scripts/extract-session.sh - JSONL 압축 (thinking, tool_use 제거)
  • ${baseDir}/references/session-file-format.md - JSONL 구조 및 파싱

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the History Insight AI skill do?

This skill should be used when user wants to access, capture, or reference Claude Code session history. Trigger when user says "capture session", "save session history", or references past/current conversation as a source - whether for saving, extracting, summarizing, or reviewing. This includes any mention of "what we discussed", "today's work", "session history", or when user treats the conversation itself as source material (e.g., "from our conversation").

Why use History Insight on TypingMind?

Because you install it once and use it with any model. History Insight is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install History Insight in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/team-attention/plugins-for-claude-natives/tree/main/plugins/session-wrap/skills/history-insight. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use History Insight?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with History Insight?

As many as you like. As long as a model supports skills, you can use History Insight with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the History Insight AI skill free?

Yes. It is published on GitHub by team-attention under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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