正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

@./AGENTS.md

rafael thayto

10,420 subscribers

37,868 次观看 • 3 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Claude Code cut about 80% of its system prompt for newer models. A research paper evaluating AGENTS.md found those files often do not improve task success while increasing inference cost by over 20%. So what DO you put in the AGENTS.md file?!

Claude Code cut about 80% of its system prompt for newer models. A research paper evaluating AGENTS.md found those files often do not improve task success while increasing inference cost by over 20%. So what DO you put in the AGENTS.md file?!

Kent C. Dodds 🐨

16,102 次观看 • 1 个月前

Copilot code review now supports AGENTS.md files. 💡 Here's how to customize for more context-aware reviews. ▶️

Copilot code review now supports AGENTS.md files. 💡 Here's how to customize for more context-aware reviews. ▶️

GitHub

103,083 次观看 • 2 个月前

My software factory = agents.md + 5 skills A software factory should be harness / model agnostic and still function the way you want it too Here's how mine works

My software factory = agents.md + 5 skills A software factory should be harness / model agnostic and still function the way you want it too Here's how mine works

Micky

47,285 次观看 • 12 天前

If you haven't set up Agents.md in Codex yet you can just copy the homework from Andrej Karpathy. Here's the exact setup (takes 2 minutes): 1. Go to his repo 2. Copy the 65-line Agents.md config 3. Paste it into Codex App → Global Custom Instructions 4. Done. You're already ahead of 90% of Codex users. It's minimalist. It's effective. Bookmark and Save it no matter. It'll be the most productive thing you will do this weekend

If you haven't set up Agents.md in Codex yet you can just copy the homework from Andrej Karpathy. Here's the exact setup (takes 2 minutes): 1. Go to his repo 2. Copy the 65-line Agents.md config 3. Paste it into Codex App → Global Custom Instructions 4. Done. You're already ahead of 90% of Codex users. It's minimalist. It's effective. Bookmark and Save it no matter. It'll be the most productive thing you will do this weekend

Avid

284,365 次观看 • 3 个月前

new project: tau, the nanogpt of agent harnesses. hackable, 5049 lines in pure rust. it > runs local tools > stores sessions as jsonl > uses AGENTS.md > supports all your favorite providers engineered with taste -

new project: tau, the nanogpt of agent harnesses. hackable, 5049 lines in pure rust. it > runs local tools > stores sessions as jsonl > uses AGENTS.md > supports all your favorite providers engineered with taste -

Elliot Arledge

18,013 次观看 • 4 个月前

脱・AIっぽい文章完全版だな。CLAUDE.mdとかAGENTS.md、Skillでも守られない部分も補完できる。

脱・AIっぽい文章完全版だな。CLAUDE.mdとかAGENTS.md、Skillでも守られない部分も補完できる。

mana｜株式会社MakeAI CEO

210,447 次观看 • 1 个月前

Someone paid $6,000 (!) to get OpenClaw setup. So I built a free, open-source alternative: > OpenClaw Operator It's an agent skill + AGENTS.md/CLAUDE.md file that gives Codex/Claude Code the playbooks + validation flow needed to configure your local OpenClaw install. You open your OpenClaw repo/workspace in your coding agent and say things like: - “set up a cron job” - “create a custom skill” - “fix my provider config” - “troubleshoot this install and validate it” Nothing magical. Uses context from the OpenClaw open-source repo + docs to provide an effective skill. Includes: - SKILL.md - AGENTS.md/CLAUDE.md - validation checklist - task playbooks Free and open source. Contributions welcome. Demo below. Repo in reply.

Someone paid $6,000 (!) to get OpenClaw setup. So I built a free, open-source alternative: > OpenClaw Operator It's an agent skill + AGENTS.md/CLAUDE.md file that gives Codex/Claude Code the playbooks + validation flow needed to configure your local OpenClaw install. You open your OpenClaw repo/workspace in your coding agent and say things like: - “set up a cron job” - “create a custom skill” - “fix my provider config” - “troubleshoot this install and validate it” Nothing magical. Uses context from the OpenClaw open-source repo + docs to provide an effective skill. Includes: - SKILL.md - AGENTS.md/CLAUDE.md - validation checklist - task playbooks Free and open source. Contributions welcome. Demo below. Repo in reply.

Dan McAteer

17,859 次观看 • 6 个月前

Our new `/ce-pov` skill is one of Compound Engineering's latest upgrades. It gives you a simple way to get a grounded, multi-model, answer to questions. It's one of my most frequently used skills rn. I'm playing with AGENTS.md instructions to figure out bestt conditions for auto invoking.

Our new `/ce-pov` skill is one of Compound Engineering's latest upgrades. It gives you a simple way to get a grounded, multi-model, answer to questions. It's one of my most frequently used skills rn. I'm playing with AGENTS.md instructions to figure out bestt conditions for auto invoking.

Trevin Chow

12,397 次观看 • 1 个月前

Speedrun Ethereum challenges are now AI-ready ✨ Each one ships with AGENTS.md full context, so any AI can answer your questions and help you go deeper. If you prefer a guided experience, use /start in Claude Code, Cursor, and most modern IDEs to activate AI Tutor Mode: concept explanations, knowledge checks, hints, and live code reviews

Speedrun Ethereum challenges are now AI-ready ✨ Each one ships with AGENTS.md full context, so any AI can answer your questions and help you go deeper. If you prefer a guided experience, use /start in Claude Code, Cursor, and most modern IDEs to activate AI Tutor Mode: concept explanations, knowledge checks, hints, and live code reviews

BuidlGuidl.eth

10,354 次观看 • 5 个月前

Pi Agent vs OpenCode token usage A lot of people recommended Pi Agent so I decided to check Pi Agent took 1.1k tokens in first turn OpenCode took 11.5k Setup: 1) Trimmed OpenCode (from usual 30k first turn to 11.5k) - 0 MCPs - 2 lightweight plugins (opencode-env-protect and openslimedit) - 8k char AGENTS.md - 11585 deepseek-v4-flash input tokens - for $0.0016 2) Vanilla Pi - 0 MCPs - 0 system prompt - 8k char AGENTS.md - 1114 kimi-k2.6 input tokens - for $0.0008 I think using better models with capped tokens per turn can keep usage nearly the same as uncontrolled DeepSeek V4 Flash? The challenge now is finding the sweet spot. Can't cap tokens if quality drops. We'll see. Video below - OpenCode vs Pi side by side "say hi back" first turns test, with OpenCode Go usage for each

Pi Agent vs OpenCode token usage A lot of people recommended Pi Agent so I decided to check Pi Agent took 1.1k tokens in first turn OpenCode took 11.5k Setup: 1) Trimmed OpenCode (from usual 30k first turn to 11.5k) - 0 MCPs - 2 lightweight plugins (opencode-env-protect and openslimedit) - 8k char AGENTS.md - 11585 deepseek-v4-flash input tokens - for $0.0016 2) Vanilla Pi - 0 MCPs - 0 system prompt - 8k char AGENTS.md - 1114 kimi-k2.6 input tokens - for $0.0008 I think using better models with capped tokens per turn can keep usage nearly the same as uncontrolled DeepSeek V4 Flash? The challenge now is finding the sweet spot. Can't cap tokens if quality drops. We'll see. Video below - OpenCode vs Pi side by side "say hi back" first turns test, with OpenCode Go usage for each

raymel 👋

208,776 次观看 • 4 个月前

还没在Codex里配置好Agents.md的可以直接来抄大神Karpathy的作业了 65行的极简配置，内容精辟有效，完全可以作为你的Agents.md全局规则起点具体怎么做：直接把仓库里的这套规范复制到Codex App的全局自定义指令部分，后续配合下面文章的方法去不断扩充、迭代规则，你的Codex使用就已经超越了大多数人仓库地址：

还没在Codex里配置好Agents.md的可以直接来抄大神Karpathy的作业了 65行的极简配置，内容精辟有效，完全可以作为你的Agents.md全局规则起点具体怎么做：直接把仓库里的这套规范复制到Codex App的全局自定义指令部分，后续配合下面文章的方法去不断扩充、迭代规则，你的Codex使用就已经超越了大多数人仓库地址：

Sac

387,801 次观看 • 3 个月前

300 AI AGENTS SHARE ONE COMPUTER AT MY PLACE -> THE ONLY LAW THEY OBEY IS A TEXT FILE This was the week agents got hands -- browsers, terminals, repos, wallets. -> Moonshot buried the answer in one sentence of the K3 blog: if you need the agent to stay inside its boundaries, write the constraints down. So I did. One AGENTS.md at the root, and three hundred Kimi K3 agents read it before every action. Five constraint types cover everything: scope, one-way doors, evidence, budget, silence. If it is not on the list, it is not available. Improvisation is off until you turn it on. Violations bounce silently, anything irreversible waits at a human gate. Hundreds of blocked attempts so far, zero escapes. Capability is what a model can do. Production is what it reliably will not. One file. Three hundred readers. The full AGENTS.md is in the article ↓

300 AI AGENTS SHARE ONE COMPUTER AT MY PLACE -> THE ONLY LAW THEY OBEY IS A TEXT FILE This was the week agents got hands -- browsers, terminals, repos, wallets. -> Moonshot buried the answer in one sentence of the K3 blog: if you need the agent to stay inside its boundaries, write the constraints down. So I did. One AGENTS.md at the root, and three hundred Kimi K3 agents read it before every action. Five constraint types cover everything: scope, one-way doors, evidence, budget, silence. If it is not on the list, it is not available. Improvisation is off until you turn it on. Violations bounce silently, anything irreversible waits at a human gate. Hundreds of blocked attempts so far, zero escapes. Capability is what a model can do. Production is what it reliably will not. One file. Three hundred readers. The full AGENTS.md is in the article ↓

slash1s

19,190 次观看 • 5 天前

Reminder: You can use Codex code review as part of your ChatGPT subscription 🙂 1. Head to 2. Connect your GitHub 3. Enable code review 4. Choose between review all PRs, just yours or trigger explicitly with "Codex magazine review this" To not spam you Codex will respond with 👍 unless it finds high priority items. You can use AGENTS.md to shape what a high priority item is.

Reminder: You can use Codex code review as part of your ChatGPT subscription 🙂 1. Head to 2. Connect your GitHub 3. Enable code review 4. Choose between review all PRs, just yours or trigger explicitly with "Codex magazine review this" To not spam you Codex will respond with 👍 unless it finds high priority items. You can use AGENTS.md to shape what a high priority item is.

dominik kundel

89,178 次观看 • 6 个月前

I was tired of using a different tool for every platform just to download a piece of media So I built Fetchz link: Supports X, YouTube, Instagram & Pinterest (MP4/MP3) Paste any public post URL → preview the media → Fetchz detects the media, loads the preview, and automatically loads the available format → download Also built the repo to be AI-native - Scoped context - AGENTS.md - Custom agentic skills - Automated browser testing - Safety rules

I was tired of using a different tool for every platform just to download a piece of media So I built Fetchz link: Supports X, YouTube, Instagram & Pinterest (MP4/MP3) Paste any public post URL → preview the media → Fetchz detects the media, loads the preview, and automatically loads the available format → download Also built the repo to be AI-native - Scoped context - AGENTS.md - Custom agentic skills - Automated browser testing - Safety rules

Bhavya

29,686 次观看 • 1 个月前

HERMES AGENT WITHOUT THESE 3 FILES IS A CHATBOT. WITH THEM IT KNOWS WHO IT IS, WHO YOU ARE, AND WHAT IT LEARNED. SOUL.md — who the agent is. first thing in the system prompt. defines personality, voice, values, how it operates, what it can and can't do. structure yours like this: → identity (name, role, relationship to you) → values (what matters, what principles guide decisions) → voice (how it communicates, tone, style) → operations (autonomy level, ground rules) → restrictions (what it never does) → failure protocol (how to operate when things break) lives in ~/.hermes/SOUL.md. auto-seeded on first install. edit anytime. scanned for prompt injection on every load. keep it concise. SOUL.md injects into every turn. a 200-line soul burns tokens on every message. aim for 50-80 lines. one paragraph per section. MEMORY.md — what the agent remembers. persistent facts, insights, preferences. survives across sessions and restarts. capped at ~800 tokens by default: memory: memory_char_limit: 2200 the agent writes to this automatically as it learns about your work. USER.md — who you are. your profile, preferences, context. capped at ~500 tokens by default: memory: user_char_limit: 1375 injected every turn so the agent always knows who it's working for. bonus: AGENTS.md — project-specific instructions. drop one in any project folder. subdirectory AGENTS.md files load lazily during tool calls, not at startup. keeps your system prompt light. prompt stack order on every turn: SOUL.md → tool guidance → MEMORY.md + USER.md → skills index → AGENTS.md → platform hints skills come preloaded. 60+ built-in tools. the agent creates more skills from completed work. you focus on these 3 files. each profile gets its own copy: ~/.hermes/SOUL.md (default profile) ~/.hermes/profiles/researcher/SOUL.md ~/.hermes/profiles/ops/SOUL.md different agent, different soul, different memory, same machine. full breakdown of Hermes as a Personal AI OS in the article 👇

YanXbt

28,924 次观看 • 3 个月前

The hottest job for the next five years is going to be the agent operator. They don't need to be an engineer. They can walk into marketing, legal, or life sciences research and actually make agents work for that function. Required skills: > MCPs > CLIs > Writing skills (the file kind) > agents.md fluency > Business acumen None of this is in any CS curriculum today. Soon, enterprises will be pressured to redesign their workflows for agents, not for people. And when that happens, agent operators will be in massive demand.

The hottest job for the next five years is going to be the agent operator. They don't need to be an engineer. They can walk into marketing, legal, or life sciences research and actually make agents work for that function. Required skills: > MCPs > CLIs > Writing skills (the file kind) > agents.md fluency > Business acumen None of this is in any CS curriculum today. Soon, enterprises will be pressured to redesign their workflows for agents, not for people. And when that happens, agent operators will be in massive demand.

rvivek

489,531 次观看 • 4 个月前

Excited to share that I've stepped into a new role as VP of the Agentic AI Foundation (AAIF) 🎉 As AI reshapes our industry, it's critical that this technology evolves in ways that are open and collaborative. Hosted by the Linux Foundation, Agentic AI Foundation is a neutral organization focused on advancing adoption of key open source efforts like MCP, AGENTS.md, and Goose. Our members include Anthropic, OpenAI, Google, AWS, Microsoft, and 100+ others. This work is bigger than any single company or product. I'm ecstatic to help drive AI adoption and interoperability at an industry-wide level.

Excited to share that I've stepped into a new role as VP of the Agentic AI Foundation (AAIF) 🎉 As AI reshapes our industry, it's critical that this technology evolves in ways that are open and collaborative. Hosted by the Linux Foundation, Agentic AI Foundation is a neutral organization focused on advancing adoption of key open source efforts like MCP, AGENTS.md, and Goose. Our members include Anthropic, OpenAI, Google, AWS, Microsoft, and 100+ others. This work is bigger than any single company or product. I'm ecstatic to help drive AI adoption and interoperability at an industry-wide level.

Angie Jones

76,169 次观看 • 5 个月前

🚨 Codex 6 Astraをメインモデルで使ってる人はまず最初にこれやってください。 OpenAI公式も正式に案内してるモデルだけ最新版にして、 AGENTS.mdやSkillsを昔のまま使っていると、 Astra本来の性能を半減してる可能性があるリプに修正プロンプト👇

🚨 Codex 6 Astraをメインモデルで使ってる人はまず最初にこれやってください。 OpenAI公式も正式に案内してるモデルだけ最新版にして、 AGENTS.mdやSkillsを昔のまま使っていると、 Astra本来の性能を半減してる可能性があるリプに修正プロンプト👇

Codex研究ラボ

159,770 次观看 • 21 小时前

HackerRank CEO 预测：未来5年最火工作 ——代理操作员「Agent Operator」！非工程师也能干！营销、法律、生命科学等等行业专家快上车——学会部署AI代理，重塑工作流，让AI替人干活！必备技能：CLI + agents.md + 结构化文件 + 商业头脑企业即将围绕AI代理重新设计一切！

HackerRank CEO 预测：未来5年最火工作 ——代理操作员「Agent Operator」！非工程师也能干！营销、法律、生命科学等等行业专家快上车——学会部署AI代理，重塑工作流，让AI替人干活！必备技能：CLI + agents.md + 结构化文件 + 商业头脑企业即将围绕AI代理重新设计一切！

KK.aWSB

27,291 次观看 • 4 个月前

I turned the Google Gemma Gemma 4 12B model into an enterprise RFP agent. Running locally in the Hugging Face Llama app and connected to Box, the agent: - pulls the RFP + approved source docs - drafts source-cited responses - flags gaps instead of hallucinating - pauses for human approval - writes the final draft back to Box The model runs locally while Box keeps the enterprise content governed. 00:22 - Demo overview 00:48 - RFP + company sources stored in Box 02:00 - Why local AI works well for confidential document workflows 02:28 - Setting up local AI with the Llama app 04:50 - Walkthrough of AGENTS.md + the script 08:07 - Running the workflow 11:12 - Conclusion

I turned the Google Gemma Gemma 4 12B model into an enterprise RFP agent. Running locally in the Hugging Face Llama app and connected to Box, the agent: - pulls the RFP + approved source docs - drafts source-cited responses - flags gaps instead of hallucinating - pauses for human approval - writes the final draft back to Box The model runs locally while Box keeps the enterprise content governed. 00:22 - Demo overview 00:48 - RFP + company sources stored in Box 02:00 - Why local AI works well for confidential document workflows 02:28 - Setting up local AI with the Llama app 04:50 - Walkthrough of AGENTS.md + the script 08:07 - Running the workflow 11:12 - Conclusion

Chris Kim

150,387 次观看 • 27 天前