Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/DjangoPeng/agentic-ainpx agentmods add skills/djangopeng/agentic-ai/morning-newspaper-assistant-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/djangopeng/agentic-ai/morning-newspaper-assistant-skill)<a href="https://agentmods.dev/skills/djangopeng/agentic-ai/morning-newspaper-assistant-skill"><img src="https://agentmods.dev/badge/skills/djangopeng/agentic-ai/morning-newspaper-assistant-skill/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/djangopeng/agentic-ai/morning-newspaper-assistant-skill"><img src="https://agentmods.dev/badge/skills/djangopeng/agentic-ai/morning-newspaper-assistant-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00054 | $0.01598 |
| Opus 5 | $0.00027 | $0.00799 |
| Sonnet 5 | $0.00011 | $0.00320 |
| Haiku 4.5 | $0.00005 | $0.00160 |
Grade A, and why
morning-newspaper-assistant-skill 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.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Morning Newspaper Assistant Skill
当用户希望运行中文 AI 晨报助手链路、生成 top10_publishable.json、输出静态页面、启动 8510 固定链接，或者排查邮箱提醒与成稿稳定性时，使用本 Skill。
项目依赖
这个 Skill 依赖完整项目仓库，不能只拷贝 SKILL.md 单独使用。
按以下顺序定位项目根目录：
- 环境变量
MORNING_NEWSPAPER_ROOT ~/projects/agentic-ai/morning-newspaper~/.openclaw/workspace/morning-newspaper
若这些路径都不存在，应明确告诉用户：当前环境尚未部署完整项目仓库，请先完成部署。
主要入口：
<repo_root>/scripts/run_daily_pipeline.py<repo_root>/config/sources.yaml
稳定目标
runtime/top10_publishable.json稳定为 10 条runtime/dashboard.html稳定可生成- 8510 固定链接稳定可用
- 右侧”今日待办提醒”优先读取真实邮箱结果，而不是占位 JSON
- 如果 IMAP 连通但收不到新邮件，自动继续走 POP3 fallback
稳定工作流
A. 每日稳定主流程
重要：不要直接执行 run_daily_pipeline.py。 该脚本是批处理入口，不会生成 LLM 结果文件。必须按以下步骤逐步执行，在每个"LLM 关口"处读取 prompt 文件、生成结果、再继续。
第一阶段：采集与准备
python3 scripts/collect_mailbox.py
python3 scripts/collect_raw.py
python3 scripts/enrich_content.py
python3 scripts/prepare_title_shortlist.py
产出：
runtime/collected_raw.jsonruntime/content_enriched.jsonruntime/title_candidates.jsonruntime/title_shortlist_prompt.txt
LLM 关口 1：标题粗筛
读取 runtime/title_shortlist_prompt.txt，按 prompt 要求生成结果，写入 runtime/title_shortlist_result.json。
必须基于本轮 title_candidates.json 生成，不能复用旧文件。
然后继续：
python3 scripts/apply_title_shortlist.py
python3 scripts/prepare_draft_input.py
产出：runtime/shortlist.json、runtime/draft_input.json、runtime/draft_prompt.txt
LLM 关口 2：中文成稿
读取 runtime/draft_prompt.txt，按 prompt 要求生成结果，写入 runtime/draft_result.json。
必须基于本轮 draft_input.json 生成，不能复用旧文件。
然后继续：
python3 scripts/apply_draft_results.py
python3 scripts/prepare_top10_ranking.py
产出：runtime/drafted_items.json、runtime/top10_ranking_input.json、runtime/top10_ranking_prompt.txt
LLM 关口 3：Top10 精排
读取 runtime/top10_ranking_prompt.txt，按 prompt 要求生成结果，写入 runtime/top10_ranking_result.json。
必须基于本轮 top10_ranking_input.json 生成，不能复用旧文件。
然后继续：
python3 scripts/apply_top10_ranking.py
python3 scripts/build_dashboard.py
python3 scripts/check_runtime_status.py
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 · 178 lines · 54 tokens per session scan A 717a6ab77508
morning-newspaper-assistant-skill is a skill published in the GitHub repository DjangoPeng/agentic-ai (148 stars, last pushed 2mo ago), licensed MIT. It adds 54 tokens to every session and 1,598 once invoked, about $0.0003 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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