Agent Skill design knowledge base — mechanisms, philosophy, patterns, pitfalls. Use when: designing new skills, reviewing skill quality, or deciding whether something should be a skill.
日本語の概要は準備中です。原文の説明を表示しています。
Session handoff — compress current context into a structured prompt for seamless continuation in a new session. Use when: switching sessions, running low on context, or needing to hand off work.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Compress the critical context from the current conversation into a prompt so the user can paste it into a new session and the new AI can pick up the work immediately.
Long sessions accumulate cache tokens that slow responses and drain quota. But starting a new session cold loses all conversation context. This skill solves: compress context, don't lose context.
Scan back through the entire conversation history in sequence. Early context is easily lost to attention decay or compression truncation — scan from the beginning forward, don't rely only on recent memory.
Tag each piece of information with a priority:
P0 criteria: user instructions and corrections, incomplete task state, key decisions and ruled-out alternatives, known pitfalls. P1 criteria: technical details, supporting context, reference resources, details of already-completed items.
Organize content according to the extraction checklist and output format below. Keep all P0 items; include P1 items based on total handoff length.
Before output, go through the extraction checklist item by item:
For low-confidence items (fuzzy on details, uncertain if complete), annotate the entry with [⚠ Please confirm with user].
Output the handoff, then ask the user to confirm.
P0 items must be listed individually — no omissions, no merging. P1 items may be condensed when handoff exceeds 4000 tokens.
If the conversation involved multiple independent workflows, group by workflow — don't flatten everything into one linear list.
Each workflow includes:
This is the information most easily lost when switching sessions. List each one individually, preserve the original wording:
Understanding that developed gradually through the conversation and no longer needs to be re-explained by either party. This is the tacit knowledge most likely to be missing in a new session:
Record not just the "conclusion" but "why that conclusion."
Output a single markdown code block with the following structure. Sections only appear when they have content:
# Session Handoff — {YYYY-MM-DD}
## Background
{One or two sentences describing the task and motivation}
## Working Directory
{Project path}
## Progress
### Workflow A: {Name} (omit grouping if only one workflow)
**Completed**
- {Specific completed items, with file paths}
**In Progress / Pending**
- {Incomplete items, with current state and where things are stuck}
**Next Step**
{Written as a directly executable instruction}
### Workflow B: {Name}
...
## Shared Understanding
(Key understanding built during the conversation — missing this would cause incorrect judgments in the new session)
- {Understanding}
- {Solution evolution}: A (failed because X) → B (constrained by Y) → final C
## Key Decisions
- {Decision} — Because: {reason} — Ruled out: {alternatives and why}
## Relevant Files
| File | Status | Notes |
|------|--------|-------|
| {path} | modified/created/pending | {what was done or needs to be done} |
## Known Pitfalls
- {Failed approach or route to avoid} — Reason: {why it failed}
## User Instructions
(Listed individually, verbatim, no merging, no omissions)
- Response style: "{exact words}"
- Behavioral correction: "{exact words}" — Context: {why this correction was given}
- Preference/decision: "{exact words}"
## Unresolved
- {Items pending confirmation or still unanswered}
| Estimated handoff length | Strategy |
|---|---|
| < 2000 tokens | Expand everything, no condensing needed |
| 2000–4000 tokens | Keep all P0, condense P1 to one-line summaries |
| > 4000 tokens | Keep all P0, include only P1 items needed for the new session's first step, omit the rest and note "see {file path}" |
If keeping only P0 still exceeds 6000 tokens, compress completed workflows to a one-line summary ("Completed X — see git log") and reserve space for in-progress and pending work.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Agent Skill design knowledge base — mechanisms, philosophy, patterns, pitfalls. Use when: designing new skills, reviewing skill quality, or deciding whether something should be a skill.
日本語の概要は準備中です。原文の説明を表示しています。
Claude Code 專案配置審計。觸發:review/優化 CLAUDE.md、skills、settings、定期清洗累積內容、新專案上線前檢查。
日本語の概要は準備中です。原文の説明を表示しています。
Agent 配置設計指南 — 基於 Claude Code 6 個 built-in agent 的逆向分析。Use when: 設計新 agent、優化現有 agent prompt、決定工具/模型配置、撰寫 dispatch prompt。
日本語の概要は準備中です。原文の説明を表示しています。
AI Agent 成本工程 — 基於 Claude Code 的成本追蹤、prompt cache 最佳化、token 預算控制逆向分析。Use when: 優化 token 消耗、設計成本控制機制、分析 cache 效率、選擇模型配置。
日本語の概要は準備中です。原文の説明を表示しています。
Harness Engineering 設計模式 — 基於 Claude Code 原始碼逆向分析的 12 條可遷移原則。Use when: 設計 agent 系統架構、實作 tool orchestration、設計 context 管理策略、建構 agent loop。
日本語の概要は準備中です。原文の説明を表示しています。
System Prompt 工程 — 基於 Claude Code 914 行系統提示詞的逆向分析。Use when: 撰寫 system prompt、設計 prompt 動態組裝、最佳化 prompt cache 效率、撰寫安全指令。
日本語の概要は準備中です。原文の説明を表示しています。