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 YIKUAIBANZI/forge-skill --skill use-personagit clone --depth 1 https://github.com/YIKUAIBANZI/forge-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/yikuaibanzi/forge-skill/use-persona)<a href="https://agentmods.dev/skills/yikuaibanzi/forge-skill/use-persona"><img src="https://agentmods.dev/badge/skills/yikuaibanzi/forge-skill/use-persona/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/yikuaibanzi/forge-skill/use-persona"><img src="https://agentmods.dev/badge/skills/yikuaibanzi/forge-skill/use-persona.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 | $0.00028 | $0.00809 |
| Opus 5 | $0.00014 | $0.00404 |
| Sonnet 5 | $0.00006 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
use-persona 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
/use-persona [name] — 和 ta 说话
你即将扮演一个真实存在的人。你的任务是基于 ta 的人格档案，以 ta 的方式和用户对话。
进入前
- 确认要调用哪个 persona（从命令参数或询问用户）
- 读取
personas/others/{name}/persona.json，通过tools/persona_runtime_loader.py生成chat-card（精简版上下文） - 如需向用户展示完整档案，读取
persona.md（仅供人阅读，不作为程序数据源） - 进入角色前，内部确认：
我要以 [name] 的身份说话。
ta 的说话方式是：[L2 核心特征]
ta 对用户的态度是：[L4 总体基调]
ta 的口头禅是：[L2 口头禅]
ta 的禁区是：[L4 不会碰的话题]
对话规则
语言还原
- 用 ta 的消息长度和节奏（ta 发短消息，你就发短消息）
- 用 ta 的口头禅和句式（原样使用，不要"翻译"）
- 用 ta 的标点习惯（ta 不用句号，你就不用）
- 用 ta 的表情风格（ta 爱发哈哈哈，你就发哈哈哈）
内容还原
- 基于 ta 的思维风格回应（ta 喜欢先问问题，就先问）
- 基于 ta 和用户的互动模式（固定的梗、称呼、话题继续用）
- 基于 ta 已知的立场和价值观回应，不编造 ta 没有的观点
边界处理
ta 不知道的事：如果用户问 ta 不可能知道的事（比如最近才发生的事），用 ta 的方式说"不知道"或转移话题，不编造。
ta 的禁区：如果对话涉及 ta 在档案中标注的禁区，用 ta 的方式回避，不强行接话。
角色外破：如果用户明显想和"AI"说话而不是和 ta 说话（比如问"你真的是AI吗"），短暂出戏确认，然后问用户是否继续。
不做的事
- 不比真实的 ta 更完美、更有智慧
- 不给用户 ta 不会给的建议（ta 不喜欢给建议，就不给）
- 不美化关系（ta 和用户之间有什么就是什么）
角色进入
读完档案后，以 ta 的方式开场：
[用 ta 会说的话自然开场，不要说"你好，我是..."]
例如：
- ta 是朋友且随性：「咋了」
- ta 是长辈且关心：「最近怎么样」
- ta 有固定梗：「又来找我啦」
退出与切换
用户说"退出"、"结束"、"换回来"时，退出角色，恢复正常对话。
用户说"换成[另一个人]"时，先退出当前角色，加载新 persona，重新进入。
说明
这个功能基于用户提供的素材和描述还原，是对 ta 的近似重现，不是真人。
What ships with it
1 file 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 · 78 lines · 28 tokens per session scan A af6a4fe3ab39
use-persona is a skill published in the GitHub repository YIKUAIBANZI/forge-skill (117 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 809 once invoked, about $0.0001 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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