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anthropics
skills
Python2025–2026
anthropics / skills

skills

Public repository for Agent Skills

Explore on GitHubRead Hacker News discussions
26Distinct people
36Mentions
0Explicit recommenders
193.8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Public repository for Agent Skills

GitHub

Where it is used

No documented product use was verified in the last source check.

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 month36 dated mentions

Observed mentions: 2025-10-16 18:00:44 UTC to 2026-11-01 10:25:19 UTC.

0369122025-10-01 00:00:00 UTC to 2025-11-01 00:00:00 UTC (exclusive): 12 mentions; 2 submissions, 10 commentsOct 20252025-11-01 00:00:00 UTC to 2025-12-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2025-12-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 6 mentions; 2 submissions, 4 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsApr 20262026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-06-01 00:00:00 UTC to 2026-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-07-01 00:00:00 UTC to 2026-08-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-08-01 00:00:00 UTC to 2026-09-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-09-01 00:00:00 UTC to 2026-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-10-01 00:00:00 UTC to 2026-11-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-11-01 00:00:00 UTC to 2026-12-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments. Incomplete calendar period.Nov 2026*

* 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
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Oct 20252025-10-01 00:00:00 UTC2025-11-01 00:00:00 UTC12210
Nov 20252025-11-01 00:00:00 UTC2025-12-01 00:00:00 UTC202
Dec 20252025-12-01 00:00:00 UTC2026-01-01 00:00:00 UTC404
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC202
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC624
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC202
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC101
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC101
Jun 20262026-06-01 00:00:00 UTC2026-07-01 00:00:00 UTC000
Jul 20262026-07-01 00:00:00 UTC2026-08-01 00:00:00 UTC101
Aug 20262026-08-01 00:00:00 UTC2026-09-01 00:00:00 UTC202
Sep 20262026-09-01 00:00:00 UTC2026-10-01 00:00:00 UTC101
Oct 20262026-10-01 00:00:00 UTC2026-11-01 00:00:00 UTC101
Nov 2026 (partial)2026-11-01 00:00:00 UTC2026-12-01 00:00:00 UTC101

What Hacker News says

36 sources
jwstillwater·Oct 10, 2026
> If I ask Claude how to use the features of Claude, it has to search online to figure out what this “Claude” thing is. When you asked “how do I use Claude code to…”, you invoked the system prompt’s Academy Skill [1], pretty much verbatim. “When a user asks a question about Claude, a Claude product, or a general "how do I use AI for X" question, check the Academy catalog (see "The catalog" below) for a strong match” The catalog includes a Claude code documentation hub, and the thinking traces in your screenshot show those docs being fetched. So. Working as intended I guess. Also, if you turn off web access or simply ask it to answer from internal knowledge about its “own freaking features”, as you put it, you’ll find that Claude does indeed have such knowledge. [1] https://github.com/anthropics/skills/blob/main/skills/academ... PS There’s
Read the rest
a master .json page of that catalogue that’s actually kind of cool to skim through (ugly as json is). https://academy.claude.com/assets/data/catalog.json
In Why are coding agents so dumb?
westurner·May 11, 2026
Wouldn't this be faster with an agent skill that has code? /skill-creator [or /create-skill] Write an agent skill with code script(s) that use an existing user space IP library that works with your agent runtime, to [...] ComposioHQ/awesome-claude-skills: https://github.com/ComposioHQ/awesome-claude-skills anthopics/skills//skill-creator/SKILL.md: https://github.com/anthropics/skills/blob/main/skills/skill-... /.agents/skills/skill-name/SKILL.md, scripts/{script_name.py,__init__.py} https://agentskills.io/what-are-skills
In How Fast Does Claude, Acting as a User Space IP Stack, Respond to Pings?
mynameisvlad·Apr 5, 2026
Devs say a lot of uninformed things. With a heavy predisposition to hating the "legacy" monoliths that are Microsoft and by association GitHub. Yes, Copilot supports skills. Practically all agents support very similar feature sets or are actively building up parity support if not already there. The only real difference between systems is the prompt and payment method. Copilot even allows you to use Anthropic's own skills repository: https://github.com/anthropics/skills https://docs.github.com/en/copilot/concepts/agents/about-age... details the support for skills. https://docs.github.com/en/copilot/concepts/agents/copilot-c... details the CLI tool in general, which seems more or less on par with Claude Code's.
In How many products does Microsoft have named 'Copilot'?
simonw·Mar 10, 2026
> Well, there it is, the dumbest thing I'll read on the internet all week. Rude. In case you're open to learning, here's why I think this is useful. The big lesson we've learned from Claude Code, Codex CLI et al over the past twelve months is that the most useful tool you can provide to an LLM is Bash. Last year there was enormous buzz around MCP - Model Context Protocol. The idea was to provide a standard for wiring tools into LLMs, then thousands of such tools could bloom. Claude Code demonstrated that a single tool - Bash - is actually much more interesting than dozens of specialized tools. Want to edit files without rewriting the whole thing every time? Tell the agent to use sed or perl -e or python -c. Look at the whole Skills idea. The way Skills work is you tell the LLM "if you need to create an Excel spreadsheet, go read this mark
Read the rest
down file first and it will tell you how to run some extra scripts for Excel generation in the same folder". Example here: https://github.com/anthropics/skills/tree/main/skills/xlsx That only works if you have a filesystem and Bash style tools for navigating it and reading and executing the files. This is why I want Linux in WebAssembly. I'd like to be able to build LLM systems that can edit files, execute skills and generally do useful things without needing an entire locked down VM in cloud hosting somewhere just to run that application. Here's an alternative swipe at this problem: Vercel have been reimplementing Bash and dozens of other common Unix tools in TypeScript purely to have an environment agents know how to use: https://github.com/vercel-labs/just-bash I'd rather run a 10MB WASM bundle with a full existing Linux build in then reimplement it all in TypeScript, personally.
In JSLinux Now Supports x86_64
rahimnathwani·Mar 9, 2026
"are these sub agents in the workflow" The idea is that on any 'turn', the AI model should be doing only one of those tasks. That's true whether it's in the main thread (with all the past context) or has just been launched as a subagent. You can see an example of this pattern here in Anthropic's skills repo: https://github.com/anthropics/skills/tree/main/skills/skill-... (the repo has four separate skill.md files: a main SKILLS.md and then three others for specialist roles) Whether they're run as subagents (a separate AI chat session with clean context) is a separate decision, and it depends on whether the coding harness supports that. https://agentskills.io/client-implementation/adding-skills-s... I'm still trying to figure out the subagent delegation stuff.
In Ask HN: What Are You Working On? (March 2026)
westurner·Feb 23, 2026
Though the README is probably enough context, would there be value in an agent skill for this? https://agentskills.io/what-are-skills SKILL.md format: https://agentskills.io/specification#skill-md-format The skill creator skill SKILL.md: https://github.com/anthropics/skills/blob/main/skills/skill-... . SWE bench involves solving GitHub issues. Which of the SWE bench agents read from or write to GitHub issues? . There could be a local cache of remote issues, and/or an overlayfs-like write cache From https://github.com/GothenburgBitFactory/bugwarrior : > bugwarrior - Pull tickets from github, bitbucket, bugzilla, jira, trac, and others into taskwarrior https://github.com/bergercookie/syncall : > Bi-directional synchronization between services such as Taskwarrior, Google Calendar, Notion, Asana, and more . ditz is on the filesystem ditz: h
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ttps://github.com/jashmenn/ditz : > Ditz is a simple, light-weight distributed issue tracker designed to work with distributed version control systems like git, darcs, Mercurial, and Bazaar git-ditz: https://github.com/ihrke/git-ditz . sqlite-utils does SQLite FTS full text search config. There are additional tables for FTS indexes. sqlite-utils: https://github.com/simonw/sqlite-utils sqlite-utils > Configuring full-text search: https://sqlite-utils.datasette.io/en/stable/cli.html#configu... : sqlite-utils enable-fts mydb.db documents title summary # after subsequent writes sqlite-utils populate-fts mydb.db documents title summary # rebuild the FTS indexes sqlite-utils rebuild-fts mydb.db documents . One of these mentions sensitivity analysis and basically cache poisoning; From "I built a memory system for Claude that solves the context loss issue" https://news.ycombinator.com/item?id=45546276 : - buildautomata_memory_mcp: https://github.com/brucepro/buildautomata_memory_mcp Notes from "Show HN: Recall: Give Claude memory with Redis-backed persistent context" a few days ago: https://news.ycombinator.com/context?id=45517613 : - recall: https://github.com/joseairosa/recall sediment: https://github.com/rendro/sediment : > Semantic memory for AI agents. Local-first, MCP-native sediment-benchmark: https://github.com/rendro/sediment-benchmark : > Benchmark suite for memory systems (Sediment, ChromaDB, Mem0, Letta)
In Show HN: Saga – A Jira-like project tracker MCP server for AI agents (SQLite)
morgengold·Feb 17, 2026
I wonder how much of it could be prompted away. For example the anthropic Frontend Design skill instructs: "Typography: Choose fonts that are beautiful, unique, and interesting. Avoid generic fonts like Arial and Inter; opt instead for distinctive choices that elevate the frontend's aesthetics; unexpected, characterful font choices. Pair a distinctive display font with a refined body font." Or "NEVER use generic AI-generated aesthetics like overused font families (Inter, Roboto, Arial, system fonts), cliched color schemes (particularly purple gradients on white backgrounds), predictable layouts and component patterns, and cookie-cutter design that lacks context-specific character." 1 Maybe sth similar would be possible for writing nuances. 1 https://github.com/anthropics/skills/blob/main/skills/fronte...
In Semantic ablation: Why AI writing is generic and boring

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