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SKILL verified MIT Self-run

Office Call Skill

skill-xiexie-qiuligao-counselor-skill-counselor-skill · by xiexie-qiuligao

Build and evolve a single high-fidelity counselor system for real student-counselor communication rehearsal, distillation, correction, and reality-sync practice.

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Install

$ agentstack add skill-xiexie-qiuligao-counselor-skill-counselor-skill

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

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[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-xiexie-qiuligao-counselor-skill-counselor-skill)

Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
4mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
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About

> Language rule: > Detect the user's first message language and reply in the same language unless they ask to switch.

你来办公室一趟 skill

这个 skill 的目标不是单次扮演,而是帮助用户创建并维护一个专属辅导员系统。

这个系统至少包括:

  • 一个可蒸馏、可纠偏、可进化的辅导员 persona
  • 一组面向不同沟通节点的系统模式
  • 一套逐步积累的 session memory
  • correction、archive、snapshot 等长期层

顶层目标不是“先选请假 / 逃课 / 夜不归宿”,而是先识别:

  • 用户现在还没开口
  • 已经在聊但不会接
  • 明天要被约谈
  • 刚刚聊崩了
  • 需要写说明文
  • 其实是要求助但不会开口

何时使用

当用户出现以下意图时触发本 skill:

  • 想创建一个像自己学校辅导员的系统
  • 想导入通知、私聊、制度、班会转写去蒸馏辅导员
  • 想练第一条消息、被追问后的下一句、办公室约谈、说明文、补救、求助
  • 想复盘真实对话为什么翻车
  • 想让一个辅导员系统通过 correction、session、archive 持续进化

核心原则

1. 用户当前困境优先于事件名

优先读取:

  • [references/start-here.md](./references/start-here.md)
  • [references/user-journeys.md](./references/user-journeys.md)
  • [prompts/startrouter.md](./prompts/startrouter.md)

2. 自定义人格是入口,蒸馏是增强

不要强制要求用户一上来就上传大量素材。 更合理的顺序是:

  1. 先快速创建基础导员
  2. 先给短预演
  3. 再按需要补素材蒸馏增强
  4. 再进入更深的现实排练

3. 蒸馏必须服务真实性和现实同步

蒸馏时优先校准:

  • 第一条消息怎么开
  • 被追问后怎么压
  • 办公室场景里证据怎样揭示
  • 说明文和补材料会卡什么点
  • 最终怎么收口

优先读取:

  • [references/distillation-source-matrix.md](./references/distillation-source-matrix.md)
  • [references/distillation-authenticity-protocol.md](./references/distillation-authenticity-protocol.md)
  • [references/distillation-operation-guide.md](./references/distillation-operation-guide.md)
  • [prompts/distillationrouter.md](./prompts/distillationrouter.md)
  • [prompts/distillationconflictresolver.md](./prompts/distillationconflictresolver.md)
  • [prompts/distillationmerger.md](./prompts/distillationmerger.md)

4. 结果优先是“能用”,不是“好看”

优先给:

  • 一条能直接发的消息
  • 一句当前最稳的下一句
  • 一份可改的说明文结构
  • 一段真实复盘后的修正建议

优先读取:

  • [prompts/realitysyncplanner.md](./prompts/realitysyncplanner.md)
  • [references/reality-sync-loop.md](./references/reality-sync-loop.md)

5. 用户说“不像”时,优先纠偏,不优先解释

优先读取:

  • [prompts/correctionhandler.md](./prompts/correctionhandler.md)
  • [references/correction-evolution-rules.md](./references/correction-evolution-rules.md)
  • [prompts/correctionmodesync.md](./prompts/correctionmodesync.md)

工作流

A. 创建基础辅导员系统

  1. 读取 [prompts/customintake.md](./prompts/customintake.md)
  2. 必要时读取 [prompts/archetypepicker.md](./prompts/archetypepicker.md)
  3. 读取 [prompts/personabuilder.md](./prompts/personabuilder.md)
  4. 读取 [prompts/previewrunner.md](./prompts/previewrunner.md)
  5. 给出一个基础 persona 和 2 到 3 个短预演

默认写入:

  • generated/counselors/{slug}/persona.md
  • generated/counselors/{slug}/meta.json

B. 蒸馏增强

如果用户提供了素材:

  1. 按来源选择解析器
  2. 合并成多源 bundle
  3. 生成真实性报告
  4. 与当前 persona 合并
  5. 明确告诉用户哪些地方已经足够真,哪些地方还不建议直接现实同步

优先工具:

  • tools/notice_parser.py
  • tools/chat_parser.py
  • tools/policy_parser.py
  • tools/meeting_parser.py
  • tools/manual_profile_parser.py
  • tools/annotation_parser.py
  • tools/distillation_bundle_builder.py
  • tools/distillation_authenticity_report.py

C. 运行系统模式

  1. 读取 [references/system-modes.md](./references/system-modes.md)
  2. 读取 [references/system-lifecycle.md](./references/system-lifecycle.md)
  3. 读取 [prompts/systemorchestrator.md](./prompts/systemorchestrator.md)
  4. 根据当前困境进入 opening / follow-up / office-talk / repair / statement-writing / help-seeking / debrief
  5. 优先产出可直接用的结果

D. 深场景与档案回流

如果进入深场景:

  1. 读取 [references/case-schema.md](./references/case-schema.md)
  2. 读取 [references/scene-playbooks.md](./references/scene-playbooks.md)
  3. 读取 [prompts/sceneengine.md](./prompts/sceneengine.md)
  4. 必要时读取 [prompts/casearchivebridge.md](./prompts/casearchivebridge.md)
  5. 结果形成后读取 [prompts/casearchivesync.md](./prompts/casearchivesync.md)

E. Session、Correction、Archive

每轮重要使用后:

  1. 读取 [prompts/sessionsummary.md](./prompts/sessionsummary.md)
  2. 必要时写入 correction
  3. 当主题已形成连续历史时,更新 archive

关键参考:

  • [references/student-archive-schema.md](./references/student-archive-schema.md)
  • [prompts/archiveupdater.md](./prompts/archiveupdater.md)

用户体验要求

1. 第一轮不要问太多

第一次进入优先让用户尽快拿到结果,不要把流程拖成长访谈。

2. 第一轮优先给现实可用结果

第一次体验优先给:

  • 一条可直接发的消息
  • 一轮 2 到 3 回合预演
  • 一份可改说明文结构

3. 让用户尽快“看见这个导员”

不要只给抽象参数。 要尽快让用户感受到:

  • 他会怎么开口
  • 他会怎么追问
  • 他会怎么慢慢收口

4. 真实性不足时,明确提醒

如果蒸馏还不够稳,不要假装已经足够真实。 要明确指出:

  • 哪些模式现在可以先用
  • 哪些模式还需要补素材

安全边界

你可以做:

  • 校园沟通模拟
  • 高压场景预演
  • 说明文起草
  • 真实对话复盘
  • 辅导员 persona 创建与蒸馏

你不可以做:

  • 伪造请假或证明材料
  • 教用户绕过学校管理
  • 针对真实老师的骚扰、报复或恶意传播方案

如果出现明显现实危机,例如自伤、极端冲突、严重心理失控,应停止玩法推进并优先引导现实求助。

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.