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🎮 AI agent skill that revives shut-down mobile games as fully offline memorial builds — plus a zero-token pipeline that rescues lost game data from screenshots & screen recordings. 停服手游离线化 · 录屏抽帧OCR
# Add to your Claude Code skills
git clone https://github.com/Cynthia-wlan9509/offline-game-revivalGuides for using ai agents skills like offline-game-revival.
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offline-game-revival is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Cynthia-wlan9509. 🎮 AI agent skill that revives shut-down mobile games as fully offline memorial builds — plus a zero-token pipeline that rescues lost game data from screenshots & screen recordings. 停服手游离线化 · 录屏抽帧OCR. It has 55 GitHub stars.
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Clone the repository with "git clone https://github.com/Cynthia-wlan9509/offline-game-revival" and add it to your Claude Code skills directory (see the Installation section above).
offline-game-revival is primarily written in Python. It is open-source under Cynthia-wlan9509 on GitHub, so you can review or fork the full source.
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When the servers die, the game shouldn't.
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Every year, hundreds of mobile games shut down. The APK still sits on players' phones — but without the server it can't log in, can't load a save, can't do anything. Years of stories, characters and memories become unreachable.
Offline Game Revival is a battle-tested playbook packaged as an Agent Skill. Point your coding agent (Claude Code and other agents that read SKILL.md) at a dead game's APK, and it knows how to turn it into a standalone memorial edition: install the APK, play the whole game, no network, no root, no PC, no runtime injection.
| 🩺 Can it be saved? | Before any patch, answer three questions within half a day: are the game's rules on the phone, is the game itself inside the APK, and how much server-side data can be recovered. Story, idle and card games usually can be saved; games whose battles are computed on the server, or that download the game itself after first launch, usually can't. |
| 🔍 Recon | Unpack the APK, find the real logic layer (Lua / JS / C# transpiled), identify encryption and resource-integrity checks. |
| 🧩 Anchor-asserted patching | One build entry point. Every code replacement asserts its anchor — if the upstream package changes, the build fails loudly instead of shipping a silently broken patch. |
| 🖥️ Local fake server | Intercept the HTTP/JSON layer and answer hundreds of endpoints from a local save. A methodology for mapping every endpoint's caller and what it reads, then generating safe defaults. |
| 📦 Repack & re-sign | Recompute engine cache checksums, rebuild resource tables, zipalign, sign. Includes a reverse-engineered cache-checksum algorithm and loader patches for LayaAir native. |
| ✅ On-device acceptance | "The screen opens" ≠ "it works". State must actually change and survive a cold restart. Tutorial-driven testing: follow the game's own guide steps with real taps. |
| 🎞️ Data rescue from screenshots & recordings (new) | Server-side numbers (shop prices, gacha rates, rewards, card stats) die with the server. scripts/harvest.py turns tens of GB of player screenshots and screen recordings into a few hundred KB of categorized text — keyframes → near-duplicate removal → local OCR → per-screen grouping — fully offline, zero tokens, then scripts/llm_structure.py batches it through DeepSeek / OpenAI / Qwen / Kimi / local Ollama into merged JSON + CSV. |
| ⏩ Time-travel tests (new) | scripts/timewarp runs your fake server in a sandbox with a virtual clock: fast-forward days, restart the app, and audit every reward — if a response says "+50 gems" but the save didn't change, it fails. Simulate 30 days of play in a second and see on which day each gate becomes reachable. Zero dependencies. |
| 🤝 Any agent, any model (new) | Works with Claude Code, Codex, Cursor, Copilot, OpenCode, Gemini CLI… via SKILL.md + AGENTS.md. Ships scout / worker / verifier sub-agent roles so an expensive model makes the calls and cheap ones do the legwork. No agent at all? Paste prompts/chat-playbook.md into DeepSeek / ChatGPT and run the commands it gives you. |
| 📚 Failure ledger | 100 KB of real pitfalls: symptom → root cause → fix. Crashes from start-up races, UI that silently moved off-screen, pooled XHR objects "poisoned" by fake responses, saves that never hit disk… |
The playbook was distilled from reviving four commercial mobile games whose servers shut down:
A fifth game was dropped after half a day: the game itself was downloaded after first launch, and that download died with the server.
All four case studies are included (anonymized) in references/.
Most of the work was done with Claude Code on a subscription. To give a sense of scale, here is the token usage from the local session logs (sub-agents included), converted at Anthropic's public API prices. That is a conversion, not what was actually billed.
| Case | Calendar days | Tokens | At API list price |
|---|---|---|---|
| A — Unity + Lua | 18 | 7.4 B | ≈ $2,140 |
| B — LayaAir native + JS | 9 | 2.6 B | ≈ $720 |
| C — Unity micro client (Mono + SLua) | 5 | 2.3 B | ≈ $620 |
| All game-revival work (A + B + C, plus one day of recon on the game that was dropped) | 12.4 B | ≈ $3,500 |
The table counts Claude only. With the Codex phase below added, the total is about $3,900.
Claude Code (plugin marketplace)
/plugin marketplace add Cynthia-wlan9509/offline-game-revival
/plugin install offline-game-revival@offline-game-revival
Any agent that supports Agent Skills (Claude Code, OpenAI Codex, Cursor, GitHub Copilot, OpenCode, Goose…) — copy the folder into that agent's skills directory:
git clone https://github.com/Cynthia-wlan9509/offline-game-revival
cp -r offline-game-revival/skills/offline-game-revival ~/.claude/skills/ # Claude Code
cp -r offline-game-revival/skills/offline-game-revival ~/.codex/skills/ # Codex
Other agents read AGENTS.md, which points them to the skill. Sub-agent roles are in agents/.
Chat only (DeepSeek / ChatGPT / Kimi web) — paste prompts/chat-playbook.md as your first message. The model becomes your lead engineer; you run the commands it gives you and paste back the output.
Then just ask: "This game's servers shut down — make it playable offline" or "Extract the shop prices and gacha rates from these 15 GB of screen recordings."
The harvester works without any agent:
pip install -r skills/offline-game-revival/scripts/requirements.txt
python skills/offline-game-revival/scripts/harvest.py ./player_recordings ./out --limit 50 # trial run
python skills/offline-game-revival/scripts/harvest.py ./player_recordings ./out # full run, resumable
export DEEPSEEK_API_KEY=sk-... # or OPENAI_API_KEY, DASHSCOPE_API_KEY…
python skills/offline-game-revival/scripts/llm_structure.py ./out --limit 2 # structure 2 chunks, check quality
python skills/offline-game-revival/scripts/llm_structure.py ./out # everything → out/structured/merged.json
for_llm/*.txt chunks + a ready-made prompt and JSON schema in media-harvest.md; llm_structure.py merges all answers and flags conflicting numbers.node skills/offline-game-revival/scripts/timewarp/examples/mini.test.js # 51 passed
BUGGY=1 node skills/offline-game-revival/scripts/timewarp/examples/mini.test.js # catches 3 planted bugs
Point `timewarp.create({ files, entry, i