SIsimonw·Jul 24, 2026
Anthropic started their in August 2023 https://github.com/anthropics/claude-cookbooks/commit/2b3f4a...
OpenAI's started in June 2022 https://github.com/openai/openai-cookbook/commit/535f545be7e...
In Claude Cookbookanthropics
claude-cookbooks
Jupyter Notebook2023–2026
anthropics / claude-cookbooks
claude-cookbooks
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
9Distinct people
12Mentions
0Explicit recommenders
54.6KGitHub stars
What to know before exploring
What it is
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
No classified warning is attached to this page. Read the discussions before treating silence as approval.
Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year12 dated mentions
Observed mentions: 2023-09-25 16:56:44 UTC to 2026-07-24 10:12:20 UTC.
* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 1 | 0 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 5 | 2 | 3 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 5 | 1 | 4 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
12 sourcesFront End Aesthetics: A Prompting Guide
1 points · Open discussionYeah, "connected" feels right to me.
Those decisions feel to me like problems for the agent harness to solve - Anthropic released a new cookbook about that yesterday: https://github.com/anthropics/claude-cookbooks/blob/main/too...
In Designing agentic loopsFrom what it looks like, it's one main LLM (you are sending query to - orchestrator) which calls other LLMs via tool calls. The tools are capable of calling llms too, and can have specific instructions, but mostly just the orchestrator deciding what they should be researching on, and assigns them specific subqueries. There is a limited depth / levels of search queries too, you should see the prompt they use[1]
One cool example of this in action is seen when you use claude code and ask it to search something. In a verbose setting, it calls an MCP tool to help with search. The tool returns summary of the results with the relevant links (not the raw search result text). A similar method, albeit more robust, is used when Claude is doing deep research as well.
[1]: https://github.com/anthropics/anthropic-cookbook/blob/main/p...
In Building Effective AI Agentslivestream here: https://youtu.be/EvtPBaaykdo
my highlights:
1. Coding ability: "Claude Opus 4 is our most powerful model yet and the best coding model in the world, leading on SWE-bench (72.5%) and Terminal-bench (43.2%). It delivers sustained performance on long-running tasks that require focused effort and thousands of steps, with the ability to work continuously for several hours—dramatically outperforming all Sonnet models and significantly expanding what AI agents can accomplish." however this is Best of N, with no transparency on size of N and how they decide the best, saying "We then use an internal scoring model to select the best candidate from the remaining attempts." Claude Code is now generally available (we covered in http://latent.space/p/claude-code )
2. Memory highlight: "Claude Opus 4 also dramatically outperforms all pr
Read the rest
evious models on memory capabilities. When developers build applications that provide Claude local file access, Opus 4 becomes skilled at creating and maintaining 'memory files' to store key information. This unlocks better long-term task awareness, coherence, and performance on agent tasks—like Opus 4 creating a 'Navigation Guide' while playing Pokémon." Memory Cookbook: https://github.com/anthropics/anthropic-cookbook/blob/main/t...
3. Raw CoT available: "we've introduced thinking summaries for Claude 4 models that use a smaller model to condense lengthy thought processes. This summarization is only needed about 5% of the time—most thought processes are short enough to display in full. Users requiring raw chains of thought for advanced prompt engineering can contact sales about our new Developer Mode to retain full access."
4. haha: "We no longer include the third ‘planning tool’ used by Claude 3.7 Sonnet. " <- psyop?
5. context caching now has a premium 1hr TTL option: "Developers can now choose between our standard 5-minute time to live (TTL) for prompt caching or opt for an extended 1-hour TTL at an additional cost"
6. https://www.anthropic.com/news/agent-capabilities-api new code execution tool (sandbox) and file tool
You can get JSON output with a JSON schema via tool use [1]. Is this not reliable like (e.g.) OpenAI's structured outputs?
[1] https://github.com/anthropics/anthropic-cookbook/blob/main/t...
In Citations on the Anthropic APIBuilding Effective AI Agents Cookbook
1 points · Open discussionThis is by far the most practical piece of writing I've seen on the subject of "agents" - it includes actionable definitions, then splits most of the value out into "workflows" and describes those in depth with example applications.
There's also a cookbook with useful code examples: https://github.com/anthropics/anthropic-cookbook/tree/main/p...
Blogged about this here: https://simonwillison.net/2024/Dec/20/building-effective-age...
In Building Effective "Agents"Those are great tips. The RAG thing looks doable. Is there a pre-fab solution, or do I need to use one of the APIs for the big-box providers?
My concern is: although it looks relatively easy to implement, I'm not sure I want to build a whole interface for it. I wish Cursor exposed, eg, this:
https://github.com/anthropics/anthropic-cookbook/blob/main/s...
In Ask HN: Have you hit a context ceiling with an LLM? What did you do about it?Anthropic have some interesting cookbook examples that provide advice on using their multimodal models here: https://github.com/anthropics/anthropic-cookbook/tree/main/m...
I've assembled a bunch more notes here: https://simonwillison.net/tags/vision-llms/
In Vision language models are blindCollection of notebooks showcasing some fun and effective ways of using Claude
128 points · Open discussion