AI Agent Skills for Chinese Knowledge Workers

Reusable agent skills for weekly review, iMandalArt, FIRE analysis, card-based notes, writing, publishing, and Chinese knowledge workflows.

iMandalArt, FIRE semantic analysis, planning, and publishing workflows for Claude Code, Codex, and mainstream LLM agents.

This repository is Yunghsi's public agent-skill system for Chinese knowledge workers. It turns repeatable writing, planning, note-making, and publishing workflows into skills that can be used by Claude Code, Codex, ChatGPT, Gemini, Hermes, and other LLM agents.

The source of truth lives in skills/*/SKILL.md; the website turns those files into generated LLM manifests, a searchable skill index, install commands, version labels, Git revisions, and update timestamps.

What This Repository Is

twhsi/skills is an installable, shareable, LLM-readable skill registry. It turns long-running workflows for weekly review, iMandalArt, FIRE analysis, card-based notes, EPUB publishing, HyperCard returns, and desktop work into public procedures that agents can repeat and humans can inspect.

The point is not to make humans behave like faster machines. The point is to let AI spend tokens on repetitive structure, while humans keep judgment, relationships, pace, and the quieter question:

Which action brings real happiness and peace?

The newest featured skill is weekly-reverse-review: it turns annual plans, hundred-year life plans, last week's review, seven days of diary notes, calendar evidence, and inbox noise into the next week's 8 Big Rocks.

Live site: https://www.twhsi.com/
Agent manifest: https://www.twhsi.com/agent.json
Skill index: https://www.twhsi.com/skills.json
LLM context: https://www.twhsi.com/llms.txt

What It Does

• Convert long Markdown notes into iMandalArt 2.01 hard-line 9-grid cards.
• Apply FIRE semantic analysis for card-box thinking, retrieval, and writing structure.
• Generate agent-readable metadata through agent.json, skills.json, and llms.txt.
• Route daily planning, weekly planning, booklet, EPUB, Markdown, and knowledge-management workflows.
• Package Chinese-first workflows so LLM agents can operate on them consistently.

Copyable Demo

Input: 200 days of daily plans, manuscript notes, or Markdown drafts
Skills: imandalart + fire-analysis-card + project-note-json-to-epub
Output: FIRE JSON + iMandalArt 2.01 card + Markdown / EPUB / booklet path

Featured: Weekly Reverse Review

weekly-reverse-review turns an 11-step weekly review into an AI-assisted reverse planning loop.

The skill reads four angles before writing the next week:

• YEAR: annual plan and hundred-year life plan.
• Week: last weekly plan and weekly review.
• Day: daily plans, seven-day diary notes, and calendar evidence.
• Inbox: loose tasks, reminders, subscriptions, errands, and collected noise.

It then asks what should be smaller, slower, deleted, delayed, or kept as presence instead of achievement. The center question is:

Which action brings real happiness and peace?

Default answer:

Speak less. Stay present. Move slowly.

For an LLM or agent, start with:

curl -s https://www.twhsi.com/llms.txt

Featured: iMandalArt 2.01

imandalart turns loose source material into one hard-line 3x3 Mandala index card.

iMandalArt 2.01 is designed around a strict text contract:

• Eight orthogonal surrounding angles labeled Ⓐ through Ⓗ.
• A double center axis displayed as ◎◎◎◎◎.
• Exactly 11 physical text lines, so the card survives chat previews, note apps, and clipboard workflows.
• Compact CJK-friendly cells for TheBrain/Cerebro, Hermes, Discord, Codex, and other LLM chat surfaces.

Current status: iMandalArt 2.01 is optimized for CJK workflows. An English-native version is planned so the same 3x3 thinking rhythm can work naturally for English notes without forcing a Chinese character contract.

Conceptual example:

ⒶHealth Reset  ⒷManuscript  ⒸMoney Noise
Move with care  Pull one center  Review first
Build rhythm    Draft before all Fund the work

ⒹFamily Spark  ◎◎◎◎◎    ⒺPeople Path
Ask not lecture Weekly Review Keep three cards
Walk the long   ◎◎◎◎◎    Connect next

ⒻInner Release ⒼLearning    ⒽJoyful Rest
Speak less      Number lines  Sing and loosen
Prove nothing   Build index   Guitar and sun

Use it for weekly planning, writing focus, knowledge capture, and CJK note workflows where visual stability matters as much as semantic compression.

What This Is

• A GitHub-backed skill registry for Chinese agent workflows.
• A machine-readable index for LLM agents that need routing, install commands, and resource discovery.
• A human-readable map for deciding which workflows should become reusable skills.
• A static website that publishes each skill's semantic version when declared, latest Git revision, and latest update time.

Core Skill Stack

Current Metadata Highlight

fire-analysis-card is now on FIRE 2.0:

• F = Full-D: stable numbering for temporary, permanent, and project notes.
• I = Index: keyword webs and retrieval handles.
• R = Route: thinking paths through the material.
• E = Evolution: time-based card-box growth for semantic search.

Skill Versions And Updates

The live website generates freshness metadata from skill files and Git history on every deployment. Each skill entry includes:

• version: the semantic skill version when declared, otherwise Unversioned
• revision and revision_short: the latest Git commit for that skill path
• updated_at: the latest update timestamp for that skill path

Open the live generated table:

• https://www.twhsi.com/#updates
• https://www.twhsi.com/skills.json

Featured metadata check: imandalart declares v2.01, and fire-analysis-card declares v2.0.

Registry Routes

Core Files

assets/      public display assets
skills/      installable skills for mainstream LLM workflows
docs/        install notes, book links, and skill index
examples/    sample inputs and outputs
archive/     older drafts and retired skills
Hermes.md    system map and command file
site/        static website source
dist/        generated website output, ignored by git

Install A Skill Locally

From the repository root:

cp -R skills/fire-analysis-card ~/.codex/skills/
cp -R skills/todays-daily-plan ~/.codex/skills/
cp -R skills/weekly-reverse-review ~/.codex/skills/
cp -R skills/imandalart ~/.codex/skills/

Then validate a skill:

python3 ~/.codex/skills/.system/skill-creator/scripts/quick_validate.py skills/fire-analysis-card

Build The Website

npm run build

The build reads skills/*/SKILL.md, extracts frontmatter, detects declared versions, asks Git for latest per-skill revision timestamps, and writes:

• dist/agent.json
• dist/skills.json
• dist/llms.txt
• the static HTML/CSS/JS site

Vercel configuration lives in vercel.json: build command npm run build, output directory dist.

Maintenance Rule

When a skill changes, update the skill file first, run validation, rebuild the website, and push to main. The live site should always show the latest skill version, revision, and update time.