dasheng-stage-intake-brief-draft
Use when executing the upstream stages (intake, brief, draft) of Dasheng workflow and producing editor-ready topic sets and standard drafts.
Skill by leecyno1
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: productivity
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/dasheng-stage-intake-brief-draft
What's inside
- Skill name
dasheng-stage-intake-brief-draft- Description
- Use when executing the upstream stages (intake, brief, draft) of Dasheng workflow and producing editor-ready topic sets and standard drafts.
- License
- MIT
- Instructions
- 107 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- openai.yaml · agents/
SKILL.md (first lines)
# Dasheng Stage: Intake + Brief + Draft
## 默认路径
- `DASHENG_WORKSPACE=${DASHENG_WORKSPACE:-${DASHENG_PROJECT_ROOT}}`
## 阶段目标
- `intake`:采集并生成来源底稿/统计报告
- `brief`:生成 8-10 个编辑候选题(人工指定题强制入池)
- `draft`:每题标准初稿(事实稿,不注入平台风格)
## 重要更新
### Brief 环节已升级为 AI 驱动
**旧系统问题**:
- 使用硬编码模板拼接生成选题标题
- 标题生硬,逻辑关系不清
- 例如:"外交部、伊朗:事件升级之外,长期秩序成本在怎样上升"
**新系统优势**:
- 使用 AI 理解事件因果关系
- 生成自然语言标题
- 提供完整的论证和证据需求
- 推荐写作框架和内容增强策略
**使用新系统**:
```bash
# 推荐:使用 dasheng-stage-brief-ai skill
# 该 skill 会生成更自然、有洞察力的选题
```
详见:`../dasheng-stage-brief-ai/SKILL.md`
### Draft 环节已集成框架系统
**新增能力**:
- 根据 brief 推荐的框架生成结构化初稿
- 应用内容增强策略(角度发现、密度强化、细节锚定、真实体感)
- 自动验证 draft 质量(字数、结构、引用等)
**使用框架驱动的 draft**:
```bash
cd "${DASHENG_WORKSPACE}"
python3 scripts/draft_with_framework.py \
--brief-dir "产物/02_Brief/2026-04-04_204231_ai" \
--output-dir "产物/03_Draft/2026-04-04_204231"
```
## 推荐命令
### Intake
```bash
cd "${DASHENG_WORKSPACE}"
python3 scripts/run_stage1_intake.py
```
### Brief(推荐使用 AI 系统)
```bash
# 方式 1:通过 skill 调用(推荐)
# 使用 dasheng-stage-brief-ai 从最新的 intake 数据生成选题
# 方式 2:直接运行旧系统(不推荐,标题生硬)
python3 scripts/phase2_rebuilder.py \
"产物/01_内容采集/2026-04-04_204231/raw/intake_records.json" \
"产物/02_Brief/2026-04-04_204231"
```
### Draft(推荐使用框架驱动)
```bash
# 方式 1:框架驱动(推荐)
python3 scripts/draft_with_framework.py \
--brief-dir "产物/02_Brief/2026-04-04_204231_ai" \
--output-dir "产物/03_Draft/2026-04-04_204231"
# 方式 2:传统方式
# 使用项目内现有的 draft 生成脚本
```
> brief / draft 使用项目内当前控制文件执行;必须遵守:
> `引擎/03_全链路SOP工作流/STAGE_INTERFACES.md`
## 交付要求
- `intake_manifest.json`
- `brief_manifest.json`(新增字段:generation_method, recommended_framework, recommended_strategy)
- `draft_manifest.json`(新增字段:framework, strategy, validation)
- 每篇初稿独立文档,便于编辑并行审核
## 强约束
1. `draft` 仅写标准事实稿,不做 DNA 改写。
2. 数据与引用必须可追溯,不能用内部统计替代外部证据。
3. 不同选题严禁混到同一正文。
4. **Brief 必须使用 AI 系统**:旧的规则系统生成的标题质量不符合要求。
5. **Draft 应遵循推荐框架**:brief 环节推荐的框架和策略应在 draft 中体现。
## 参考文档
- Brief AI 生成指南:`../dasheng-stage-brief-ai/references/ai-generation-guide.md`
- 选题评估框架:`../dasheng-stage-brief-ai/references/topic-evaluation.md`
- 写作框架:`../dasheng-stage-rewrite/references/frameworks.md`
- 内容增强策略:`../dasheng-stage-rewrite/references/content-enhance.md`From leecyno1/newma-media-studio, MIT.
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Signals
- Stars
- 5
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- Aug 3, 2026 (2 months ago)
- Last release
- Aug 3, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/leecyno1/newma-media-studio
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
dasheng-stage-intake-brief-draft skill. Agent Mart. https://agentmart.dev/skills/leecyno1-dasheng-stage-intake-brief-draft (last updated 2026-10-24)