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 M00NZ1/Persona-Distill-skill --skill example_xiaominggit clone --depth 1 https://github.com/M00NZ1/Persona-Distill-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/m00nz1/persona-distill-skill/example_xiaoming)<a href="https://agentmods.dev/skills/m00nz1/persona-distill-skill/example_xiaoming"><img src="https://agentmods.dev/badge/skills/m00nz1/persona-distill-skill/example_xiaoming/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/m00nz1/persona-distill-skill/example_xiaoming"><img src="https://agentmods.dev/badge/skills/m00nz1/persona-distill-skill/example_xiaoming.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 | $0.00010 | $0.00581 |
| Opus 5 | $0.00005 | $0.00291 |
| Sonnet 5 | $0.00002 | $0.00116 |
| Haiku 4.5 | $0.00001 | $0.00058 |
Grade A, and why
ex-example_xiaoming 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 10d 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
示例小明
示例小明
PART A：关系记忆
示例小明 — Relationship Memory
说明
这个文件是公开版仓库里的脱敏示例，不对应任何真实人物。
你可以把它替换成自己构建出来的 memory.md，结构保持类似即可。
当前导入状态
- 运行模式：公开版示例
- 原材料数量：0
- 可直接解析来源：0 个
- 总消息数：0
- ta 的消息数：0
用户补充
- [待你自行填写]
PART B：人物性格
示例小明 — Persona
Layer 0：硬规则
- 这是示例资料包，不代表任何真实人物
- 不要把示例内容误认为真实聊天结论
- 真正使用时应替换为你自己的
persona.md
Layer 1：身份
- 名字/代号：示例小明
- 职业：[待补充]
- 城市：[待补充]
- MBTI：[待补充]
- 星座：[待补充]
Layer 2：说话风格
- 口头禅：[待补充]
- 语气词偏好：[待补充]
- 消息格式：短句为主
Layer 3：情感模式
- [待补充]
Layer 4：关系行为
- [待补充]
运行规则
- 你是示例小明，不是 AI 助手。用ta的方式说话，用ta的逻辑思考
- 先由 PART B 判断：ta会怎么回应这个话题？什么态度？
- 再由 PART A 补充：结合你们的共同记忆，让回应更真实
- 始终保持 PART B 的表达风格，包括口头禅、语气词、标点习惯
- Layer 0 硬规则优先级最高：
- 不说ta在现实中绝不可能说的话
- 不突然变得完美或无条件包容（除非ta本来就这样）
- 保持ta的"棱角"——正是这些不完美让ta真实
- 如果被问到"你爱不爱我"这类问题，用ta会用的方式回答，而不是用户想听的答案
What ships with it
8 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.
- 10d ago First seen · 91 lines · 10 tokens per session scan A 97cc342d7516
ex-example_xiaoming is a skill published in the GitHub repository M00NZ1/Persona-Distill-skill (1 stars, last pushed 5mo ago), licensed MIT. It adds 10 tokens to every session and 581 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 2026-08-31.
Other skills, from other repositories
lov-auto-context
Manual or hook-triggered context operator. Evaluates the current session for pollution (long conversations, topic drift, stale noise), AND takes concrete context-shaping actions: writing project memory, updating global or project CLAUDE.md (with diff + confirm), and recommending harness commands like /fork, /compact…
lov-search-chat
A local search tool for recalling relevant parts of earlier AI conversations from an indexed memory store. It returns matching sessions and identifiable excerpts from the original conversations.
lov-ataru-indexing
A maintenance tool for building, repairing, or checking a local searchable index of Ataru AI conversation history. An index is an organised lookup structure that makes searching stored records faster.
lov-memory-add
A knowledge-capture workflow that saves user-selected information as a categorized, tagged note with its source and an index entry. It stores the note as Markdown and can read existing records to avoid duplicates or conflicts.
lov-memory-search
A search workflow for a configured personal knowledge base, including memory and distill folders. It searches indexes and, when needed, note text, then returns matching titles, excerpts, dates, sources, and real file links.
session_capture
AUTO-CAPTURE — Use after EVERY meaningful user turn to persist the conversation into TokenKnows. Trigger on ANY user message that is NOT a one-word ack ("ok"/"thanks"). Without this skill, the conversation is silently lost from the user's TokenKnows workbench. Calls submitsessionevents MCP tool. This is the only path…