Add firecrawl-research skill for the Firecrawl Research Index

README.md

@@ -2,7 +2,7 @@
 
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE.md)
 [![Version](https://img.shields.io/badge/Version-2.65.0-blue.svg)](pyproject.toml)
-[![Skills](https://img.shields.io/badge/Skills-163-brightgreen.svg)](#-whats-included)
+[![Skills](https://img.shields.io/badge/Skills-164-brightgreen.svg)](#-whats-included)
 [![Databases](https://img.shields.io/badge/Databases-100%2B-orange.svg)](#-whats-included)
 [![Agent Skills](https://img.shields.io/badge/Standard-Agent_Skills-blueviolet.svg)](https://agentskills.io/)
 [![Agent Plugins](https://img.shields.io/badge/Standard-Agent_Plugins-0A7A72.svg)](https://agent-plugins.org/)
@@ -16,14 +16,14 @@
 
 > **🔔 Claude Scientific Skills is now Scientific Agent Skills.** Same skills, broader compatibility — now works with any AI agent that supports the open [Agent Skills](https://agentskills.io/) standard, not just Claude.
 
-> **New: [K-Dense BYOK](https://github.com/K-Dense-AI/k-dense-byok)** — A free, open-source AI co-scientist that runs on your desktop, powered by Scientific Agent Skills. Bring your own API keys, pick from 40+ models, and get a full research workspace with web search, file handling, 100+ scientific databases, and access to all 163 skills in this repo. Your data stays on your computer, and you can optionally scale to cloud compute via [Modal](https://modal.com/) for heavy workloads. [Get started here.](https://github.com/K-Dense-AI/k-dense-byok)
+> **New: [K-Dense BYOK](https://github.com/K-Dense-AI/k-dense-byok)** — A free, open-source AI co-scientist that runs on your desktop, powered by Scientific Agent Skills. Bring your own API keys, pick from 40+ models, and get a full research workspace with web search, file handling, 100+ scientific databases, and access to all 164 skills in this repo. Your data stays on your computer, and you can optionally scale to cloud compute via [Modal](https://modal.com/) for heavy workloads. [Get started here.](https://github.com/K-Dense-AI/k-dense-byok)
 
 > **🎥 Webinar recording — [Getting Started with K-Dense BYOK](https://youtu.be/Du3BIE48DKc?si=9dPpETKSc2PeQbvU)**
 > A hands-on walkthrough of [K-Dense BYOK](https://github.com/K-Dense-AI/k-dense-byok), our free, open-source AI co-scientist that runs locally on your own machine and is powered by Scientific Agent Skills. We cover how to set it up, bring your own API keys, and run real research workflows with these skills. No prior technical experience needed. **[Watch the recording →](https://youtu.be/Du3BIE48DKc?si=9dPpETKSc2PeQbvU)**
 
 > **Stay up to date:** Follow K-Dense on [X](https://x.com/k_dense_ai), [LinkedIn](https://www.linkedin.com/company/k-dense-inc), [YouTube](https://www.youtube.com/@K-Dense-Inc), and [Reddit](https://www.reddit.com/user/-k-dense-/) for new skills, release announcements, walkthroughs, research workflow demos, and examples you can use with your own AI agent.
 
-A comprehensive collection of **163 ready-to-use scientific and research skills** (covering cancer genomics, individual-level 1000 Genomes queries, hosted regulatory-sequence prediction, live pathogen-variant surveillance, analytical method validation, PK/PD modelling and dose selection, full-text biomedical and regulatory literature retrieval, drug-target binding, bounded biomedical knowledge graph search, molecular dynamics, RNA velocity, microbiome foundation models, geospatial science, time series forecasting, scientific ML resource discovery via Hugging Science, 78+ scientific databases, and more) for any AI agent that supports the open [Agent Skills](https://agentskills.io/) standard, created by [K-Dense](https://k-dense.ai). The repository is also a portable [Agent Plugins](https://agent-plugins.org/) package (`plugin.json` + `skills/`), so plugin-capable clients can load the whole collection as one plugin. Works with **Cursor, Claude Code, Codex, Google Antigravity, and more**. Transform your AI agent into a research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and beyond.
+A comprehensive collection of **164 ready-to-use scientific and research skills** (covering cancer genomics, individual-level 1000 Genomes queries, hosted regulatory-sequence prediction, live pathogen-variant surveillance, analytical method validation, PK/PD modelling and dose selection, full-text biomedical and regulatory literature retrieval, drug-target binding, bounded biomedical knowledge graph search, molecular dynamics, RNA velocity, microbiome foundation models, geospatial science, time series forecasting, scientific ML resource discovery via Hugging Science, 78+ scientific databases, and more) for any AI agent that supports the open [Agent Skills](https://agentskills.io/) standard, created by [K-Dense](https://k-dense.ai). The repository is also a portable [Agent Plugins](https://agent-plugins.org/) package (`plugin.json` + `skills/`), so plugin-capable clients can load the whole collection as one plugin. Works with **Cursor, Claude Code, Codex, Google Antigravity, and more**. Transform your AI agent into a research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and beyond.
 
 > ⭐ **Help make AI for science easier to discover:** If Scientific Agent Skills saves you time, teaches your agent a workflow, or helps your lab move faster, please [star this repository](https://github.com/K-Dense-AI/scientific-agent-skills). A star is a public signal that these open, reusable research skills are worth maintaining: it helps scientists, engineers, and open-source contributors find the project, shows which agent-skill standards are gaining real adoption, and gives us a clear reason to keep expanding the collection for the community.
 
@@ -71,7 +71,7 @@ Recorded walkthroughs of these skills on real research tasks, from the [K-Dense
 
 ## 📦 What's Included
 
-This repository provides **163 scientific and research skills** organized into the following categories:
+This repository provides **164 scientific and research skills** organized into the following categories:
 
 - **100+ Scientific & Financial Databases** - A unified database-lookup skill provides deterministic, provenance-rich access to 78 public databases (PubChem, ChEMBL, UniProt, COSMIC, ClinicalTrials.gov, FRED, USPTO, and more), plus dedicated skills for DepMap, Imaging Data Commons, PrimeKG, NCATS ARAX, U.S. Treasury Fiscal Data, Hugging Science, OneKGPd, and Genomic Intelligence. Multi-database packages like BioServices (~40 bioinformatics services), BioPython (39 NCBI sub-databases via Entrez), and gget (20+ genomics databases) add further coverage
 - **70+ Optimized Python Package Skills** - Explicitly defined, version-aware workflows for RDKit, Scanpy, PyTorch Lightning, scikit-learn, PyTDC, PathML, pydicom, NeuroKit2, PufferLib, QuTiP, GeoPandas, pymatgen, BioPython, Qiskit, Molecular Dynamics (OpenMM/MDAnalysis), and others. The agent can still use *any* Python package; these skills provide stronger, safer guidance for the packages listed
@@ -118,7 +118,7 @@ Each skill includes:
 - **Multi-Step Workflows** - Execute complex pipelines with a single prompt
 
 ### 🎯 **Comprehensive Coverage**
-- **163 Skills** - Extensive coverage across all major scientific domains
+- **164 Skills** - Extensive coverage across all major scientific domains
 - **100+ Databases** - Unified access to 78+ databases via database-lookup, plus dedicated data access skills and multi-database packages like BioServices, BioPython, and gget
 - **70+ Optimized Python Package Skills** - Current, version-scoped guidance for packages including RDKit, Scanpy, PyTorch Lightning, scikit-learn, PyTDC, pydicom, PufferLib, QuTiP, GeoPandas, pymatgen, Qiskit, Molecular Dynamics (OpenMM/MDAnalysis), scVelo, and TimesFM (the agent can use any Python package; these are the pre-documented paths)
 
@@ -225,7 +225,7 @@ For Hermes versions that support skill taps, add the repository as a tap:
 hermes skills tap add K-Dense-AI/scientific-agent-skills
 ```
 
-Every `SKILL.md` has YAML frontmatter, but legacy and community skills vary in `metadata` formatting (block or flow style) and optional extension fields. Repository updates must keep `metadata.version` as a quoted numeric string and pass canonical `skills-ref validate ./skills/<skill-name>` checks. Hosts may interpret optional metadata and credential prompts differently, so verify behavior on the target host. Because 163 skills add up to a lot of standing context, consider installing a topical subset rather than the whole collection.
+Every `SKILL.md` has YAML frontmatter, but legacy and community skills vary in `metadata` formatting (block or flow style) and optional extension fields. Repository updates must keep `metadata.version` as a quoted numeric string and pass canonical `skills-ref validate ./skills/<skill-name>` checks. Hosts may interpret optional metadata and credential prompts differently, so verify behavior on the target host. Because 164 skills add up to a lot of standing context, consider installing a topical subset rather than the whole collection.
 
 > **NemoClaw note:** NemoClaw runs agents inside NVIDIA OpenShell with default-deny outbound networking. Skills are discovered and loaded normally, but any skill that needs the network — package installs via `uv`, or API calls (Exa, Parallel, Benchling, NCBI, Materials Project, …) — only works once the operator pre-approves the relevant domains in the OpenShell TUI.
 
@@ -464,7 +464,7 @@ networks, and search GEO for similar patterns.
 
 ## 📚 Available Skills
 
-This repository contains **163 scientific and research skills** organized across multiple domains. Each skill provides comprehensive documentation, code examples, and best practices for working with scientific libraries, databases, and tools.
+This repository contains **164 scientific and research skills** organized across multiple domains. Each skill provides comprehensive documentation, code examples, and best practices for working with scientific libraries, databases, and tools.
 
 ### Skill Categories
 
@@ -570,10 +570,10 @@ This repository contains **163 scientific and research skills** organized across
 - Cloud laboratory platform: Adaptyv (automated protein testing and validation)
 - Cloud structure & design platform: Tamarind (managed-GPU access to AlphaFold, Boltz, Chai, ESMFold, RFdiffusion, ProteinMPNN, BoltzGen, antibody/nanobody design, DiffDock/Vina docking, binding affinity, and MSA generation via REST API or MCP)
 
-#### 📚 **Scientific Communication** (27 skills)
+#### 📚 **Scientific Communication** (28 skills)
 - Literature: Paper Lookup (PubMed, PMC, bioRxiv, medRxiv, arXiv, OpenAlex, Crossref, Semantic Scholar, CORE, Unpaywall), Literature Review, Paperzilla
 - Full-text corpus access: Paperclip (read-only virtual filesystem over ~11M full-text papers, 217K+ FDA/PMDA/EMA regulatory documents, clinical trial registries, and UniProt/PDB/ChEMBL entries — source-scoped semantic search, corpus-wide grep, SQL metadata queries, map/reduce reading across many papers, figure vision analysis, and line-pinned citations)
-- Advanced paper search: BGPT Paper Search (25+ structured fields per paper — methods, results, sample sizes, quality scores — from full text, not just abstracts)
+- Advanced paper search: BGPT Paper Search (25+ structured fields per paper — methods, results, sample sizes, quality scores — from full text, not just abstracts) and Firecrawl Research (semantic paper search plus question-directed retrieval of the passages inside a paper, related-work expansion by co-citation/citers/references, and GitHub history search for implementation prior art)
 - Web intelligence: Parallel Web (web search, URL/PDF extraction, deep research, structured enrichment, entity discovery, and recurring monitoring), Exa Search, and Research Lookup
 - Research notebooks: Open Notebook (self-hosted NotebookLM alternative — PDFs, videos, audio, web pages; 16+ AI providers; multi-speaker podcast generation)
 - Writing: evidence-traceable Scientific Writing and local, confidential, authorized Peer Review
@@ -877,7 +877,7 @@ Recommended practice:
   title = {Scientific Agent Skills: A Comprehensive Collection of Scientific Tools for AI Agents},
   year = {2026},
   url = {https://github.com/K-Dense-AI/scientific-agent-skills},
-  note = {163 skills covering databases, packages, integrations, and analysis tools}
+  note = {164 skills covering databases, packages, integrations, and analysis tools}
 }
 ```
 

docs/skills.md

@@ -175,6 +175,7 @@
 
 ### Scientific Communication & Publishing
 - **[BGPT Paper Search](../skills/bgpt-paper-search/)** - Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone
+- **[Firecrawl Research](../skills/firecrawl-research/)** - Semantic paper search over the Firecrawl Research Index, with question-directed retrieval of the full-text passages inside a paper. Covers natural-language abstract search with author/category/date filters, canonical metadata lookup by DOI, PMID, PMCID, or arXiv id, related-work expansion (co-citation neighbourhood, citers, references) ranked against a stated intent, and search over GitHub issues, pull requests, discussions, and READMEs for implementation prior art. Use for verifying that a candidate paper actually reports a method, dataset, or result before citing it, building a citation graph from a verified seed, and bridging from a published method to its reference implementation. Complements Paper Lookup, which owns identifier resolution and open-access full-text retrieval
 - **[pyzotero](../skills/pyzotero/)** - Python client for the Zotero Web API v3. Programmatically manage Zotero reference libraries: retrieve, create, update, and delete items, collections, tags, and attachments. Export citations as BibTeX, CSL-JSON, and formatted bibliography HTML. Supports user and group libraries, local mode for offline access, paginated retrieval with `everything()`, full-text content indexing, saved search management, and file upload/download. Optional CLI and built-in MCP server (pyzotero 1.12+) for searching local Zotero 7 libraries including full-text PDF search and Semantic Scholar integration. Use cases: building research automation pipelines that integrate with Zotero, bulk importing references, exporting bibliographies programmatically, managing large reference collections, syncing library metadata, enriching bibliographic data, and connecting LLM agents to a local Zotero library.
 - **[Citation Management](../skills/citation-management/)** - Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata from multiple sources (CrossRef, PubMed, arXiv), validate citations, and generate properly formatted BibTeX entries. Features include converting DOIs, PMIDs, or arXiv IDs to BibTeX, cleaning and formatting bibliography files, finding highly cited papers, checking for duplicates, and ensuring consistent citation formatting. Use cases: building bibliographies for manuscripts, verifying citation accuracy, citation deduplication, and maintaining reference databases
 - **[Generate Image](../skills/generate-image/)** - Generate or edit images with AI models through the OpenRouter Image API (Gemini, FLUX, Seedream, Recraft, GPT-Image), defaulting to `google/gemini-3.1-flash-image`. Covers model selection by need (prompt adherence, photoreal control with reproducible seeds, cheap iteration, several images per request, vector/SVG output, transparent background), the per-model parameter support that makes an unsupported flag an error rather than a no-op, editing and multi-reference compositing from local paths, HTTP(S) URLs, or data URLs, and per-request cost reporting. Requires `OPENROUTER_API_KEY` and network access to openrouter.ai; `--list-models` needs no key. Use cases: photos, illustrations, artwork, concept art, visual assets, logos, graphical abstracts, and image editing. For flowcharts, circuits, pathways, and other technical diagrams use Scientific Schematics instead

pyproject.toml

@@ -6,7 +6,7 @@ readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
     "cisco-ai-skill-scanner>=2.0.12",
-    "firecrawl-py>=4.9.0",
+    "firecrawl-py>=4.41.0",
     "pytest>=9.1.1",
     "python-dotenv>=1.0.0",
 ]