本文へ移動
cccskills
無料GitHub で公開

context-transfer

Generate a state document (context transfer) that allows any fresh AI instance to resume work without conversation history. Use this skill whenever the user asks to checkpoint, create a state transfer, save state, generate a handoff document, create compaction insurance, or says anything like 'snapshot this', 'create a context transfer', 'checkpoint', 'save state for handoff', 'write a recovery doc', or 'transfer context'. Also trigger when the user mentions compaction concerns, session handoff, multi-session continuity, or wants to preserve the current conversation's state. Works for any conversation type: projects, research, debugging, investigations, design sessions, or long-running chats. This skill produces a structured markdown document optimized for AI cold-start recovery, not human notes.

インストール方法を見る

含まれるファイル(2)

  • SKILL.md4.7 KB
  • references/protocol_v2.4s.md7.7 KB

SKILL.md(原文)

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。

Context Transfer

Generate structured state documents for AI cold-start recovery across any conversation type.

When To Use

  • User asks to checkpoint, snapshot, or save state
  • Session is getting long and compaction insurance is needed
  • Work will continue in a new session (handoff)
  • Multi-session work needs persistent state
  • User mentions compaction, context loss, or continuity concerns
  • Any conversation where accumulated decisions, findings, or state would be costly to lose

Before Starting

Read the full protocol:

Read references/protocol_v2.4s.md

This contains the complete section definitions, templates, rules, and quality checklist.

Quick Reference

The context transfer has 11 sections. Scale to complexity — not every conversation needs all sections.

SectionPurposeRequired?
I. What This IsIdentity + "It is NOT" correctionAlways
II. Domain ContextProblem-space briefingMulti-session+
III. ArchitectureSystem structureBuild/engineering work
IV. DecisionsNumbered with narrative WHYWhen decisions exist
V. Current StateStep sequence or phase summaryAlways
VI. ArtifactsFile inventory with statusWhen files exist
VII. Anti-Drift WarningsObserved/predicted failure modesMulti-session+
VIII. What NOT To DoCatastrophic prohibitionsWhen applicable
IX. GlossaryContext-specific termsDomain-specific
X. Open QuestionsUnresolved issuesWhen they exist
XI. Recovery PointerExact restart location + pathAlways

Minimum viable: Sections I, V, XI.

Workflow

  1. Read the protocol (references/protocol_v2.4s.md) — understand all section rules
  2. Assess scope — use Scaling Guide to determine which sections are needed
  3. Gather state from conversation — extract decisions, current step, artifacts, open questions
  4. Write each section following the protocol templates exactly
  5. Apply critical rules:
    • §I must include "It is NOT..." correction sentence
    • §IV decisions must have narrative WHY (mark [inferred] if rationale not explicitly stated)
    • §VII every warning tagged [observed] or [predicted]
    • §XI must include Work lives in: (write UNKNOWN — ask user if path not known)
  6. Run Quality Checklist from protocol
  7. Save to /mnt/user-data/outputs/ and present to user

Output

Save as: [topic_or_project]_context_transfer.md in /mnt/user-data/outputs/

The document header should include:

# Context Transfer — [Topic or Project Name]

**Version:** [N]
**Updated:** [date]
**Purpose:** Compaction insurance. If you just got compacted, read this first.

Key Rules (from protocol)

These are the rules most likely to be missed. Full rules are in the protocol reference.

  • Single source of truth: One context transfer per conversation/project. Never maintain parallel state docs.
  • Correction sentence: §I must state what it IS then what it is NOT.
  • Narrative WHY: §IV uses prose, not tables. Tables compress reasoning too much for cold start.
  • Inferred rationale: If WHY isn't explicitly stated, mark as [inferred] — never present inference as ground truth.
  • Tag all warnings: §VII requires [observed] or [predicted] on every warning. No untagged.
  • Never fabricate paths: §XI Work lives in: must be real or UNKNOWN — ask user.
  • Update immediately: Write to file after each decision/state change. Don't batch.

Notes

  • This skill is validated across Claude, GPT, and Gemini cold instances (n=5 tests, zero operational failures)
  • The protocol is model-agnostic — works without cognitive scaffolding
  • Optimized for AI pattern recognition, not human readability
  • The context transfer IS the conversation's memory — treat it as critical infrastructure

レビュー

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。

同じリポジトリのスキル

概要と使いどころ

Complete architecture reference for the A3 insurance platform — file locations, data flow, conventions, microservice map, and fullstack patterns

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Drafts U.S. commercial real estate access and indemnity (right-of-entry) agreements for pre-closing due diligence. Covers license grants, non-invasive vs invasive testing gates, insurance/endorsement requirements, indemnity with discovery carve-outs, restoration and lien remedies, confidentiality, and anti-indemnity guardrails. Trigger: access agreement, right of entry, due diligence access, Phase I/II, invasive testing, pre-PSA site inspection.

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

当用户需要对意外险投保问卷进行专业、结构化的核保审查,提取职业类别、工作环境、作业内容、危险活动参与情况、交通出行习惯、特殊工作暴露及其他可能影响意外险承保判断的高风险信息,并生成适合意外险核保、补问流转和风险分层处理的结构化分析结果时使用本 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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Inspect, schema, and fill true AcroForm PDFs using sciClaw's pdf_form_inspect, pdf_form_schema, and pdf_form_fill tools. Use when: (1) checking whether a PDF is a real fillable AcroForm, (2) listing form field names, types, and choices, (3) filling a supported form from structured values, (4) preparing reviewable insurance, legal, administrative, or clinical form drafts, (5) reporting skipped fields or unused input keys after a fill. Do not use for scanned PDFs, OCR tasks, or XFA-only forms.

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Guide actuarial analysis for insurance pricing. TRIGGERS - Use when user needs help with actuarial-analysis related tasks.

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards. USE THIS SKILL WHEN: - You need to review or audit actuarial models (reserving, pricing, capital) - Someone asks about loss triangle analysis or reserve adequacy - You are evaluating IBNR calculations, chain ladder methods, or Bornhuetter-Ferguson - A project involves insurance pricing, GLM rating models, or ratemaking - You need to assess Solvency II SCR calculations or RBC compliance - Someone mentions actuarial opinions, ASOP compliance, or SOA standards - You are reviewing stochastic models, ESG configurations, or DFA frameworks - A codebase uses actuarial libraries (chainladder, lifetables, ChainLadder R package) TRIGGER PHRASES: "actuarial", "loss reserving", "IBNR", "chain ladder", "premium pricing", "mortality table", "Solvency II", "capital adequacy", "ratemaking", "GLM pricing", "risk-based capital", "reserve analysis", "actuarial opinion"

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

FDU-INS のスキルをすべて見る

このスキルの問題を報告する