cheat-on-content
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
Create Pydantic models following the multi-model pattern for clean API contracts.
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill pydantic-models-py --agent claude-codeHow it fires
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Create Pydantic models following the multi-model pattern for clean API contracts.
name: pydantic-models-py description: "Create Pydantic models following the multi-model pattern for clean API contracts." risk: unknown source: community date_added: "2026-02-27"
Create Pydantic models following the multi-model pattern for clean API contracts.
Copy the template from assets/template.py and replace placeholders:
| Model | Purpose | |-------|---------| | `Base` | Common fields shared across models | | `Create` | Request body for creation (required fields) | | `Update` | Request body for updates (all optional) | | `Response` | API response with all fields | | `InDB` | Database document with `doc_type` |
class MyModel(BaseModel):
workspace_id: str = Field(..., alias="workspaceId")
created_at: datetime = Field(..., alias="createdAt")
class Config:
populate_by_name = True # Accept both snake_case and camelCaseclass MyUpdate(BaseModel):
"""All fields optional for PATCH requests."""
name: Optional[str] = Field(None, min_length=1)
description: Optional[str] = Noneclass MyInDB(MyResponse):
"""Adds doc_type for Cosmos DB queries."""
doc_type: str = "my_resource"1. Create models in `src/backend/app/models/` 2. Export from `src/backend/app/models/__init__.py` 3. Add corresponding TypeScript types
This skill is applicable to execute the workflow or actions described in the overview.
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Repo: LiHongwei-cn/lihongwei-cn
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric 是循环的内容,不是循环本身**——当前内置一份观点视频 rubric(参考博主 25+…
提议并执行 rubric 或 bucket 升级。两种模式:**完整 rubric bump**(最高风险动作,5 步强制 + 跨模型审核)和 **--bucket-only 轻量重校**(只换 bucket 边界,不动 rubric 公式)。**Phase 2 强制走 cheat-score-blind…
cheat-on-content 的首次 onboarding 与脚手架创建器。统一流程——所有用户都走相同 5 阶段闭环,唯一区别是"发过视频的人"会在 init 时多一步:抓取已有视频建立历史 context(用于后续 cheat-seed 给更贴合的选题、更准的…
从对标账号导入 script + 数据 → 拆 pattern + 派生 base rubric 信号 → 写到 benchmark.md / script_patterns.md / rubric_notes.md。**这是工具最早期信号的来源**——cold-start…
把老用户的 .cheat-state.json 升级到当前 schema_version。读 migrations/registry.md 算迁移链,按顺序应用每一步迁移文件。幂等:跑两次结果一样。失败停在中间版本不前进。触发词:"迁移"/"升级 state"/"migrate"/"我的 state…
从复盘评论数据派生 / 刷新账号的受众画像,写入 audience.md。这是和 rubric 平行的第二个派生物——rubric 答"怎么打分",persona 答"谁在看"。cheat-seed 选题 / 写稿时读它。**audience.md 含实绩信号,cheat-score-blind…