REPO·RANK #0·0/6 firing·Python
Rank#0Python
Cross-signal0.00 / 6.0
Quiet across tracked channels.
Cross-signal · 30D+0
GitHubQUIET+0 stars24h
HackerNewsQUIET0 posts7d
RedditQUIET0 posts7d
BlueskyQUIET0 posts7d
Dev.toQUIET0 posts7d
XQUIET0 posts7d
Stars23.5k+0 7d+0 today
Forks2.5k+0 7d11% fork ratio
Contribs0+0 30dsolo-led
Momentum0.00.0stars-velocity score
SurfaceTHIN1 / 6last commit
Coverage1 / 13 sources fired (7d)
·
K-Dense-AI/scientific-agent-skills sits at 23,548 GitHub stars with steady Python traction — organic growth keeps it on the trending list.
// 01 · GITHUB MOMENTUM
0.0
0 stars 24h | 0 7d
// 02 · MENTIONS
0
0 in 24h | 1 source
// 03 · CROSS-SIGNAL
0.00
0/6 channels firing
// 04 · PACKAGE ADOPTION
-
no linked package yet
// 05 · PROJECT SURFACE
thin
last commit
// 01
Breakdown
How is this scored?
- 6.0
- strong signal across ≥5 of 6 channels
- 5.0
- strong signal across ≥4 of 6 channels
- 4.0
- strong signal across ≥3 of 6 channels
- 3.0+
- active on 2+ channels
- <1.0
- low or no cross-channel activity
Each channel contributes 0-1. Per-channel tiers: GitHub (breakout 1.0 / hot 0.7 / rising 0.4), HN (front-page 1.0 / ≥3 mentions 0.7 / 1-2 mentions 0.4), Bluesky (≥5 mentions 1.0 / 2-4 0.7 / 1 0.4), dev.to (≥3 articles 1.0 / 2 0.7 / 1 0.4), Reddit (corpus-normalized 48h velocity), X (≥10 mentions 24h 1.0 / 3-9 0.7 / 1-2 0.4).
- GitHub momentum0.00
- Reddit0.00
- HackerNews0.00
- Bluesky0.70
- dev.to0.00
- X (Twitter)1.00
* Reddit bar shows a per-repo velocity proxy (raw score / 100); the score formula uses the corpus-normalized version so a single repo's bar may not match its contribution to the corpus-wide ranking.
// KNOWN REPO · PACKAGE · LAUNCH · SITE SURFACES
GitHubK-Dense-AI/scientific-agent-skills23.5k starsWebsitek-dense.aisite found; profile scan queued
Docspendingdocs scanner pending
npmnoneno linked npm package
ProductHuntnoneno launch linked
Paper/modelpendingHF/arXiv resolver not attached yet
AISO scan
Scan queued — refresh to check status.
// 02
Growth
No daily star history collected yet.open star-activity →
Today
0
+0 last 24h
7d
+0
rolling
30d
+0
rolling
Spike
none
no breakout in window
// 03
Mentions
// last scanreddit 14mhn 17mbluesky 46mdevto 4hph 46mnpm 3h
- X→ OPEN
Evolved Hermes into an autonomous 'AI Scientist'.🧪🧬 Integrated @k_dense_ai 's Scientific Agent Skills: 134+ primitives across 17 domains. 🛠️⚡️ Skip the docs & just do the science. Hermes PR: github.com/NousResearch/herm… cc @NousResearch @Teknium @TimothyKassis▶ Twitter - X→ OPEN
Your AI agent does what its skills tell it to. That's powerful and risky. We've started publishing security scan results for every skill in scientific-agent-skills using @CiscoSecure AI Defense Skill Scanner. We'll address findings as they surface. Open source means open accountability. Full report here: github.com/K-Dense-AI/scient…▶ Twitter - X→ OPEN
We just released an updated skill for Parallel Web Systems ( @p0 ) as part of our Scientific Agent Skills ecosystem. Now your agent scientist can use the Parallel CLI to perform search, deep search, webpage extraction and data enrichment. Also available in K-Dense BYOK and K-Dense Web. Check it out! github.com/K-Dense-AI/scient…▶ Twitter - X→ OPEN
You can now install Scientific Agent Skills with the GitHub CLI. More info here: github.blog/changelog/2026-0…▶ Twitter - X→ OPEN
If you want to let AI agents touch patient data, proprietary molecules, or pre-publication datasets, the runtime matters as much as the model. Breakdown of pairing @nvidia OpenShell's policy-governed sandbox with 133 open Scientific Agent Skills, with worked examples. k-dense.ai/blog/sandboxed-ai…▶ Twitter - X→ OPEN
Work on our Scientific Agent Skills never stops. Turn your Cursor, Claude Code, Codex, Claude CoWork into a full AI co-scientist running on your own computer. Free and open source. If you don't want to deal with setup use our hosted more powerful platform K-Dense Web!▶ Twitter - X→ OPEN
Our office hour is happening in 10 min. Join if you have question so Scientific Agent Skills, K-Dense BYOK, K-Dense Enterprise or K-Dense Web. luma.com/n6dgdqi6▶ Twitter - X→ OPEN
Nueva actualización de Ateneo-KB, inspirada en parte por ideas del repo `scientific-agent-skills` de @KDenseAI. Thanks @k_dense_ai Ahora la ingesta raw preserva original + procedencia, `MarkItDown` pasa a ser el default para PDF y añadí `search trails` reproducibles antes de curar una fuente. Lo importante no es la automatización: gana el investigador. Menos fricción para localizar y convertir; más control humano para decidir qué cuenta como evidencia, qué queda como lectura y qué sigue abierto. Gracias por compartir ese trabajo. github.com/pablomartinezmake…▶ Twitter - X→ OPEN
scientific-agent-skills is basically a library of ready-made procedural skills for scientific AI agents. Not “knowledge” in the abstract, but packaged ways to actually do work: step-by-step task routines the agent can follow inside real scientific workflows. The repo currently includes 133 ready-to-use skills, is built around the open Agent Skills standard, and is meant to work with agents like Cursor, Claude Code, and Codex. The important part is the abstraction layer. Instead of telling an LLM “analyze this dataset” and hoping it improvises well, you give it a skill that already encodes which libraries to use, what sequence of steps to follow, and what kind of output to return. That is why this kind of project matters: it turns an agent from a generic text model into something closer to a reproducible scientific operator. And the coverage is broad enough to be genuinely useful: genomics, drug discovery, molecular dynamics, clinical research, medical imaging, geospatial science, time-series forecasting, scientific writing, and access to 78+ scientific databases through unified lookup tooling. Each skill comes with a SKILL.md, examples, use cases, and integration guidance. In practice, this is exactly the layer that sits between “LLM can write code” and “agent can reliably do science.” github.com/K-Dense-AI/scient… #AI #AIAgents #ScientificAI #OpenSource #Bioinformatics #DrugDiscovery #MachineLearning #LLM #ResearchTools #ClaudeCode▶ Twitter - X→ OPEN
Claude Scientific Skills is now Scientific Agent Skills! 150K+ scientists worldwide. 17.8K GitHub stars. Support for every major platform: Claude Code, Codex, Claude CoWork, Cursor and powering K-Dense Web. Same mission. Bigger reach. github.com/K-Dense-AI/scient…▶ Twitter
// 04
Context
- United States of America
- www.k-dense.ai
- @k_dense_ai
- 10 public repos
- 972 followers
- OthmanAdi/planning-with-filesPython · 21.5k stars
Claude Code skill implementing Manus-style persistent markdown planning — the workflow pattern behind the $2B acquisition.
- romainsimon/paperassePython · 1.8k stars
🇫🇷 Skills pour agents IA spécialisés dans la bureaucratie française : Comptable, Notaire, ...
- elementalsouls/Claude-OSINTPython · 1.3k stars
Two paired Claude skills · 90+ recon modules · 48 secret-regex patterns · 80+ dorks · 9 read-only credential validators · 27 attack-path templates · 5,500+ lines of structured tradecraft. Drop-in SKILL.md files that turn Claude into a god-mode external recon operator for authorized red-team and bug-bounty engagements.
- himself65/finance-skillsTypeScript · 2.2k stars
A collection of skills for AI financial analysis and trading.
- VRSEN/OpenSwarmPython · 2.4k stars
Claude code for everything except coding
- luongnv89/claude-howtoPython · 33.2k stars
A visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value.
// 05Deep dive
// STARS23.5k—/ 7d
// FORKS2.5k—/ 7d
// CONTRIBUTORS0—/ 30d
Open Issues40
Last Commit
Latest Release—
// TREND24h07d030d0
X
Ranked confirmation layer for repo-specific X buzz in the last 24h.
Mentions 24h
12
Authors 24h
7
Engagement
675
Peak hour
08:08
Score
84.3
Meaningful X activity confirmed. 12 matched posts across 7 authors.
Top matched posts
- @k_dense_ai390 eng
Claude Scientific Skills is now Scientific Agent Skills! 150K+ scientists worldwide. 17.8K GitHub stars. Support for every major platform: Claude Code, Codex, Claude CoWork, Cursor and powering K-Dense Web. Same mission. Bigger reach. github.com/K-Dense-AI/scient…
mediumphrase24d agoopenReturned by a high-confidence repo query and contains a visible project phrase, but the exact URL, slug, or package name was not visible.
- @ruffy0369142 eng
Evolved Hermes into an autonomous 'AI Scientist'.🧪🧬 Integrated @k_dense_ai 's Scientific Agent Skills: 134+ primitives across 17 domains. 🛠️⚡️ Skip the docs & just do the science. Hermes PR: github.com/NousResearch/herm… cc @NousResearch @Teknium @TimothyKassis
mediumphrase24d agoopenMatched through a repo-specific project phrase query.
- @k_dense_ai62 eng
Your AI agent does what its skills tell it to. That's powerful and risky. We've started publishing security scan results for every skill in scientific-agent-skills using @CiscoSecure AI Defense Skill Scanner. We'll address findings as they surface. Open source means open accountability. Full report here: github.com/K-Dense-AI/scient…
mediumphrase24d agoopenMatched through a repo-specific project phrase query.
- @k_dense_ai31 eng
We just released an updated skill for Parallel Web Systems ( @p0 ) as part of our Scientific Agent Skills ecosystem. Now your agent scientist can use the Parallel CLI to perform search, deep search, webpage extraction and data enrichment. Also available in K-Dense BYOK and K-Dense Web. Check it out! github.com/K-Dense-AI/scient…
mediumphrase24d agoopenMatched through a repo-specific project phrase query.
- @k_dense_ai18 eng
You can now install Scientific Agent Skills with the GitHub CLI. More info here: github.blog/changelog/2026-0…
mediumphrase24d agoopenMatched through a repo-specific project phrase query.
- @k_dense_ai16 eng
If you want to let AI agents touch patient data, proprietary molecules, or pre-publication datasets, the runtime matters as much as the model. Breakdown of pairing @nvidia OpenShell's policy-governed sandbox with 133 open Scientific Agent Skills, with worked examples. k-dense.ai/blog/sandboxed-ai…
mediumphrase24d agoopenMatched through a repo-specific project phrase query.
- @TimothyKassis11 eng
Work on our Scientific Agent Skills never stops. Turn your Cursor, Claude Code, Codex, Claude CoWork into a full AI co-scientist running on your own computer. Free and open source. If you don't want to deal with setup use our hosted more powerful platform K-Dense Web!
mediumphrase24d agoopenMatched through a repo-specific project phrase query.
- @k_dense_ai4 eng
Our office hour is happening in 10 min. Join if you have question so Scientific Agent Skills, K-Dense BYOK, K-Dense Enterprise or K-Dense Web. luma.com/n6dgdqi6
mediumphrase24d agoopenMatched through a repo-specific project phrase query.
- @cabofaropablo1 eng
Nueva actualización de Ateneo-KB, inspirada en parte por ideas del repo `scientific-agent-skills` de @KDenseAI. Thanks @k_dense_ai Ahora la ingesta raw preserva original + procedencia, `MarkItDown` pasa a ser el default para PDF y añadí `search trails` reproducibles antes de curar una fuente. Lo importante no es la automatización: gana el investigador. Menos fricción para localizar y convertir; más control humano para decidir qué cuenta como evidencia, qué queda como lectura y qué sigue abierto. Gracias por compartir ese trabajo. github.com/pablomartinezmake…
mediumphrase24d agoopenMatched through a repo-specific project phrase query.
- @yaelkroy0 eng
scientific-agent-skills is basically a library of ready-made procedural skills for scientific AI agents. Not “knowledge” in the abstract, but packaged ways to actually do work: step-by-step task routines the agent can follow inside real scientific workflows. The repo currently includes 133 ready-to-use skills, is built around the open Agent Skills standard, and is meant to work with agents like Cursor, Claude Code, and Codex. The important part is the abstraction layer. Instead of telling an LLM “analyze this dataset” and hoping it improvises well, you give it a skill that already encodes which libraries to use, what sequence of steps to follow, and what kind of output to return. That is why this kind of project matters: it turns an agent from a generic text model into something closer to a reproducible scientific operator. And the coverage is broad enough to be genuinely useful: genomics, drug discovery, molecular dynamics, clinical research, medical imaging, geospatial science, time-series forecasting, scientific writing, and access to 78+ scientific databases through unified lookup tooling. Each skill comes with a SKILL.md, examples, use cases, and integration guidance. In practice, this is exactly the layer that sits between “LLM can write code” and “agent can reliably do science.” github.com/K-Dense-AI/scient… #AI #AIAgents #ScientificAI #OpenSource #Bioinformatics #DrugDiscovery #MachineLearning #LLM #ResearchTools #ClaudeCode
mediumphrase24d agoopenMatched through a repo-specific project phrase query.