DeerFlow is an open-source super-agent harness that coordinates sub-agents, memory, tools, sandboxes, and extensible skills to handle research, coding, and content-creation tasks that may run for minutes or hours. It is intended for long-running, multi-step work performed by AI agents. The catalogue entries are skills, agents, and instructions that support its workflows.
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 bytedance/deer-flow --skill newsletter-generationgit clone --depth 1 https://github.com/bytedance/deer-flowWrote 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/bytedance/deer-flow/newsletter-generation)<a href="https://agentmods.dev/skills/bytedance/deer-flow/newsletter-generation"><img src="https://agentmods.dev/badge/skills/bytedance/deer-flow/newsletter-generation/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/bytedance/deer-flow/newsletter-generation"><img src="https://agentmods.dev/badge/skills/bytedance/deer-flow/newsletter-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- 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 | $0.00088 | $0.02877 |
| Opus 5 | $0.00044 | $0.01438 |
| Sonnet 5 | $0.00018 | $0.00575 |
| Haiku 4.5 | $0.00009 | $0.00288 |
Grade A, and why
newsletter-generation 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- newsletter-generation — 100% identical, 0 lines differ
- newsletter-generation — 100% identical, 0 lines differ
- newsletter-generation — 100% identical, 0 lines differ
- newsletter-generation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Newsletter Generation Skill
Overview
This skill generates professional, well-researched newsletters that combine curated content from multiple sources with original analysis and commentary. It follows modern newsletter best practices from publications like Morning Brew, The Hustle, TLDR, and Benedict Evans to produce content that is informative, engaging, and actionable.
The output is a complete, ready-to-publish newsletter in Markdown format, suitable for email distribution platforms, web publishing, or conversion to HTML.
Core Capabilities
- Research and curate content from multiple web sources on specified topics
- Generate topic-focused or multi-topic newsletters with consistent voice
- Write engaging headlines, summaries, and original commentary
- Structure content for optimal readability and scanning
- Support multiple newsletter formats (daily digest, weekly roundup, deep-dive, industry briefing)
- Include relevant links, sources, and attributions
- Adapt tone and style to target audience (technical, executive, general)
- Generate recurring newsletter series with consistent branding and structure
When to Use This Skill
Always load this skill when:
- User asks to generate a newsletter, email digest, or content roundup
- User requests a curated summary of news or developments on a topic
- User wants to create a recurring newsletter format
- User asks to compile recent developments in a field into a briefing
- User needs a formatted email-ready content piece with multiple curated items
- User asks for a "weekly roundup", "monthly digest", or "morning briefing"
Newsletter Workflow
Phase 1: Planning
Step 1.1: Understand Newsletter Requirements
Identify the key parameters:
| Parameter | Description | Default |
|---|---|---|
| Topic(s) | Primary subject area(s) to cover | Required |
| Format | Daily digest, weekly roundup, deep-dive, or industry briefing | Weekly roundup |
| Target Audience | Technical, executive, general, or niche community | General |
| Tone | Professional, conversational, witty, or analytical | Conversational-professional |
| Length | Short (5-min read), medium (10-min), long (15-min+) | Medium |
| Sections | Number and type of content sections | 4-6 sections |
| Frequency Context | One-time or part of a recurring series | One-time |
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 · 344 lines · 88 tokens per session scan A cc66adb99053
newsletter-generation is a skill published in the GitHub repository bytedance/deer-flow (82,290 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 2,877 once invoked, about $0.0004 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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