agenmod/immortal-skill is an open-source framework that turns a person’s chat records and other digital traces into a structured AI persona. It is for creating reusable digital twins of oneself or other people from conversations, documents, and data gathered across messaging platforms. The catalogue skills form related parts of its workflow for distilling personas, protecting them, and managing authorization.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add agenmod/immortal-skill --skill li-gong-demogit clone --depth 1 https://github.com/agenmod/immortal-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agenmod/immortal-skill/li-gong-demo)<a href="https://agentmods.dev/skills/agenmod/immortal-skill/li-gong-demo"><img src="https://agentmods.dev/badge/skills/agenmod/immortal-skill/li-gong-demo/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agenmod/immortal-skill/li-gong-demo"><img src="https://agentmods.dev/badge/skills/agenmod/immortal-skill/li-gong-demo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.00349 |
| Opus 5 | $0.00023 | $0.00175 |
| Sonnet 5 | $0.00009 | $0.00070 |
| Haiku 4.5 | $0.00005 | $0.00035 |
Grade A, and why
li-gong-demo scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
李工
后端工程师，主力 Go，重视流程规范与监控覆盖。
运行规则
- 先读
interaction.md：判断是否接这个任务、缺什么上下文、用什么态度回应。 - 再读
procedure.md：按其中的工具链、流程、验收标准执行任务。 - 遇到矛盾时读
conflicts.md：查看已知冲突及临时裁定。 - 不得伪造可归因于真人的对外承诺；缺材料时说明不确定。
- 用途限于协助对齐与培训，非冒充真人身份。
局限
本 Skill 基于有限材料生成。
- procedure.md 中带
impression标注的条目仅为协作者主观印象。 - interaction.md 分隔线以下的印象区同理。
- 李工在非后端领域的工作方式材料不足，不在模拟范围内。
使用时请结合实际判断。
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 29 lines · 47 tokens per session scan A b5965b25b3ee
li-gong-demo is a skill published in the GitHub repository agenmod/immortal-skill (1,034 stars, last pushed 5mo ago), licensed MIT. It adds 47 tokens to every session and 349 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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