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@@ -2,9 +2,9 @@
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title: "Scientific Agent Skills"
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task: ""
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lineage_type: import
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/fc0b9f69/README.md
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upstream_sha: fc0b9f69
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||||
imported_at: 2026-07-14
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/README.md
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upstream_sha: 831d49eb
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||||
imported_at: 2026-07-21
|
||||
prompt_class: catalogue
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||||
upstream_changes: accepted
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author: upstream
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@@ -26,7 +26,13 @@ validated: false
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## Star History
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||||
[](https://www.star-history.com/#K-Dense-AI/scientific-agent-skills&type=date&legend=top-left)
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<a href="https://www.star-history.com/?repos=K-Dense-AI%2Fscientific-agent-skills&type=date&legend=top-left">
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<picture>
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||||
<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=K-Dense-AI/scientific-agent-skills&type=date&theme=dark&legend=top-left&sealed_token=rL_5GLS9f4Fbyr1_VYZLGMF-8Rr6ZlWNaYNecajc52QSQq6KL7HrzSea_tGQGy1mBMXgVvAUMSIYAc0w39si9v5Up1RIw74-UDGZg_9HvH_chiyS0Njf-5tebtPh1LJjXTG6mH5Iv2pMJNivgfPsyB-oOgbaIV3uSc7DzSeZFCTE4WOcHX4y2BR76k5g" />
|
||||
<source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=K-Dense-AI/scientific-agent-skills&type=date&legend=top-left&sealed_token=rL_5GLS9f4Fbyr1_VYZLGMF-8Rr6ZlWNaYNecajc52QSQq6KL7HrzSea_tGQGy1mBMXgVvAUMSIYAc0w39si9v5Up1RIw74-UDGZg_9HvH_chiyS0Njf-5tebtPh1LJjXTG6mH5Iv2pMJNivgfPsyB-oOgbaIV3uSc7DzSeZFCTE4WOcHX4y2BR76k5g" />
|
||||
<img alt="Star History Chart" src="https://api.star-history.com/chart?repos=K-Dense-AI/scientific-agent-skills&type=date&legend=top-left&sealed_token=rL_5GLS9f4Fbyr1_VYZLGMF-8Rr6ZlWNaYNecajc52QSQq6KL7HrzSea_tGQGy1mBMXgVvAUMSIYAc0w39si9v5Up1RIw74-UDGZg_9HvH_chiyS0Njf-5tebtPh1LJjXTG6mH5Iv2pMJNivgfPsyB-oOgbaIV3uSc7DzSeZFCTE4WOcHX4y2BR76k5g" />
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</picture>
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</a>
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> **🔔 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.
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@@ -529,7 +535,7 @@ This repository contains **148 scientific and research skills** organized across
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- Diagrams: Scientific Schematics, Markdown & Mermaid Writing
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- Infographics: Infographics (10 types, 8 styles, colorblind-safe palettes)
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- Citations: Citation Management, pyzotero
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- Illustration: Generate Image (AI image generation with FLUX.2 Pro and Gemini 3 Pro (Nano Banana Pro))
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- Illustration: Generate Image (AI image generation with FLUX.2 Pro and Gemini 3.6 Flash (Nano Banana Pro))
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#### 🔬 **Scientific Databases & Data Access** (6 skills → 100+ databases total)
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> A unified database-lookup skill provides deterministic REST API access to 78 public databases across all domains, with retrieval contracts, pagination/count reconciliation, and endpoint provenance. Dedicated skills cover specialized data platforms. Multi-database packages like BioServices (~40 bioinformatics services), BioPython (38 NCBI sub-databases via Entrez), and gget (20+ genomics databases) add further coverage.
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@@ -2,9 +2,9 @@
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title: "Scientific Skills"
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task: ""
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lineage_type: import
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/fc0b9f69/docs/skills.md
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upstream_sha: fc0b9f69
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||||
imported_at: 2026-07-14
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||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/docs/skills.md
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upstream_sha: 831d49eb
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imported_at: 2026-07-21
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||||
prompt_class: catalogue
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||||
upstream_changes: accepted
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||||
author: upstream
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@@ -175,12 +175,12 @@ validated: false
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- **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
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- **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.
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- **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
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- **Generate Image** - AI-powered image generation and editing for scientific illustrations, schematics, and visualizations using OpenRouter's image generation models. Supports multiple models including google/gemini-3-pro-image-preview (high quality, recommended default) and black-forest-labs/flux.2-pro (fast, high quality). Key features include: text-to-image generation from detailed prompts, image editing capabilities (modify existing images with natural language instructions), automatic base64 encoding/decoding, PNG output with configurable paths, and comprehensive error handling. Requires OpenRouter API key (via .env file or environment variable). Use cases: generating scientific diagrams and illustrations, creating publication-quality figures, editing existing images (changing colors, adding elements, removing backgrounds), producing schematics for papers and presentations, visualizing experimental setups, creating graphical abstracts, and generating conceptual illustrations for scientific communication
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- **Infographics** - Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes
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||||
- **Generate Image** - AI-powered image generation and editing for scientific illustrations, schematics, and visualizations using OpenRouter's image generation models. Supports multiple models including google/gemini-3.6-flash (high quality, recommended default) and black-forest-labs/flux.2-pro (fast, high quality). Key features include: text-to-image generation from detailed prompts, image editing capabilities (modify existing images with natural language instructions), automatic base64 encoding/decoding, PNG output with configurable paths, and comprehensive error handling. Requires OpenRouter API key (via .env file or environment variable). Use cases: generating scientific diagrams and illustrations, creating publication-quality figures, editing existing images (changing colors, adding elements, removing backgrounds), producing schematics for papers and presentations, visualizing experimental setups, creating graphical abstracts, and generating conceptual illustrations for scientific communication
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||||
- **Infographics** - Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes
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||||
- **LaTeX Posters** - Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication with layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices. Features compliance with conference size requirements (A0, A1, 36×48"), complex multi-column layouts, and integration of figures, tables, equations, and citations. Use cases: conference poster sessions, thesis defenses, symposia presentations, and research group templates
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||||
- **Market Research Reports** - Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation, deep integration with research-lookup for data gathering, and multi-framework strategic analysis including Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix. Use cases: investment decisions, strategic planning, competitive landscape analysis, market sizing, and market entry evaluation
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- **PPTX Posters** - Create professional research posters using PowerPoint/HTML formats for researchers who prefer WYSIWYG tools over LaTeX. Features design principles, layout templates, quality checklists, and export guidance for poster sessions. Use cases: conference posters when LaTeX is not preferred, quick poster creation, and collaborative poster design
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||||
- **Scientific Schematics** - Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review with document-type-specific thresholds (journal: 8.5/10, conference: 8.0/10, poster: 7.0/10). Specializes in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations. Features natural language input, automatic quality assessment, and publication-ready output. Use cases: creating figures for papers, generating workflow diagrams, visualizing experimental designs, and producing graphical abstracts
|
||||
- **Scientific Schematics** - Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review with document-type-specific thresholds (journal: 8.5/10, conference: 8.0/10, poster: 7.0/10). Specializes in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations. Features natural language input, automatic quality assessment, and publication-ready output. Use cases: creating figures for papers, generating workflow diagrams, visualizing experimental designs, and producing graphical abstracts
|
||||
- **Scientific Slides** - Build slide decks and presentations for research talks using PowerPoint and LaTeX Beamer. Features slide structure, design templates, timing guidance, and visual validation. Emphasizes visual engagement with minimal text, research-backed content with proper citations, and story-driven narrative. Use cases: conference presentations, academic seminars, thesis defenses, grant pitches, and professional talks
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- **Venue Templates** - Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). Provides ready-to-use templates and detailed specifications for successful academic submissions. Use cases: manuscript preparation, conference papers, research posters, and grant proposals with venue-specific formatting
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+4
-4
@@ -1,8 +1,8 @@
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||||
---
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||||
lineage_type: import
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||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/clinical-reports/SKILL.md
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||||
upstream_sha: 9c9bd2e9
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||||
imported_at: 2026-06-26
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||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/clinical-reports/SKILL.md
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||||
upstream_sha: 831d49eb
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||||
imported_at: 2026-07-21
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||||
prompt_class: unknown
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||||
upstream_changes: accepted
|
||||
name: clinical-reports
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||||
@@ -10,7 +10,7 @@ description: Write comprehensive clinical reports including case reports (CARE g
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allowed-tools: Read Write Edit Bash
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||||
license: MIT License
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
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||||
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||||
# Clinical Report Writing
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||||
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||||
+4
-4
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||||
---
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||||
lineage_type: import
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||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/literature-review/SKILL.md
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upstream_sha: 9c9bd2e9
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||||
imported_at: 2026-06-27
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||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/literature-review/SKILL.md
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||||
upstream_sha: 831d49eb
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imported_at: 2026-07-21
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prompt_class: catalogue
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upstream_changes: accepted
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name: literature-review
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||||
@@ -10,7 +10,7 @@ description: Conduct comprehensive, systematic literature reviews using multiple
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allowed-tools: Read Write Edit Bash
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||||
license: MIT license
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||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
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||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
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||||
metadata: {"version": "1.3", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
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||||
---
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||||
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# Literature Review
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@@ -1,8 +1,8 @@
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---
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lineage_type: import
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/peer-review/SKILL.md
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upstream_sha: 9c9bd2e9
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imported_at: 2026-06-27
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||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/peer-review/SKILL.md
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upstream_sha: 831d49eb
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imported_at: 2026-07-21
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prompt_class: unknown
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upstream_changes: accepted
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name: peer-review
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@@ -10,7 +10,7 @@ description: Structured manuscript/grant review with checklist-based evaluation.
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allowed-tools: Read Write Edit Bash
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||||
license: MIT license
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||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
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||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
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||||
metadata: {"version": "1.3", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
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||||
---
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||||
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# Scientific Critical Evaluation and Peer Review
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@@ -1,8 +1,8 @@
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---
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lineage_type: import
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/pptx-posters/SKILL.md
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upstream_sha: 9c9bd2e9
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imported_at: 2026-06-27
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/pptx-posters/SKILL.md
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upstream_sha: 831d49eb
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imported_at: 2026-07-21
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prompt_class: catalogue
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upstream_changes: accepted
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name: pptx-posters
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@@ -10,7 +10,7 @@ description: Create research posters using HTML/CSS that can be exported to PDF
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allowed-tools: Read Write Edit Bash
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license: MIT license
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required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
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metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
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metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
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||||
---
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||||
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# PPTX Research Posters (HTML-Based)
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---
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lineage_type: import
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/scholar-evaluation/SKILL.md
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upstream_sha: 9c9bd2e9
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||||
imported_at: 2026-06-27
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upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/scholar-evaluation/SKILL.md
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upstream_sha: 831d49eb
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imported_at: 2026-07-21
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prompt_class: unknown
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upstream_changes: accepted
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name: scholar-evaluation
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||||
description: Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.
|
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license: MIT license
|
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required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
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||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
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||||
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||||
# Scholar Evaluation
|
||||
|
||||
+14
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||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/scientific-schematics/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/scientific-schematics/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: catalogue
|
||||
upstream_changes: accepted
|
||||
name: scientific-schematics
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||||
description: Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
|
||||
description: Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
|
||||
allowed-tools: Read Write Edit Bash
|
||||
license: MIT license
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# Scientific Schematics and Diagrams
|
||||
|
||||
## Overview
|
||||
|
||||
Scientific schematics and diagrams transform complex concepts into clear visual representations for publication. **This skill uses Nano Banana 2 AI for diagram generation with Gemini 3.1 Pro Preview quality review.**
|
||||
Scientific schematics and diagrams transform complex concepts into clear visual representations for publication. **This skill uses Nano Banana 2 AI for diagram generation with Gemini 3.6 Flash quality review.**
|
||||
|
||||
**How it works:**
|
||||
- Describe your diagram in natural language
|
||||
- Nano Banana 2 generates publication-quality images automatically
|
||||
- **Gemini 3.1 Pro Preview reviews quality** against document-type thresholds
|
||||
- **Gemini 3.6 Flash reviews quality** against document-type thresholds
|
||||
- **Smart iteration**: Only regenerates if quality is below threshold
|
||||
- Publication-ready output in minutes
|
||||
- No coding, templates, or manual drawing required
|
||||
@@ -62,7 +62,7 @@ python scripts/generate_schematic.py "Complex circuit diagram with op-amp, resis
|
||||
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||||
**What happens behind the scenes:**
|
||||
1. **Generation 1**: Nano Banana 2 creates initial image following scientific diagram best practices
|
||||
2. **Review 1**: **Gemini 3.1 Pro Preview** evaluates quality against document-type threshold
|
||||
2. **Review 1**: **Gemini 3.6 Flash** evaluates quality against document-type threshold
|
||||
3. **Decision**: If quality >= threshold → **DONE** (no more iterations needed!)
|
||||
4. **If below threshold**: Improved prompt based on critique, regenerate
|
||||
5. **Repeat**: Until quality meets threshold OR max iterations reached
|
||||
@@ -156,7 +156,7 @@ python scripts/generate_schematic.py "your diagram description" -o output.png
|
||||
|
||||
---
|
||||
|
||||
# AI Generation Mode (Nano Banana 2 + Gemini 3.1 Pro Preview Review)
|
||||
# AI Generation Mode (Nano Banana 2 + Gemini 3.6 Flash Review)
|
||||
|
||||
## Smart Iterative Refinement Workflow
|
||||
|
||||
@@ -168,7 +168,7 @@ The AI generation system uses **smart iteration** - it only regenerates if quali
|
||||
┌─────────────────────────────────────────────────────┐
|
||||
│ 1. Generate image with Nano Banana 2 │
|
||||
│ ↓ │
|
||||
│ 2. Review quality with Gemini 3.1 Pro Preview │
|
||||
│ 2. Review quality with Gemini 3.6 Flash │
|
||||
│ ↓ │
|
||||
│ 3. Score >= threshold? │
|
||||
│ YES → DONE! (early stop) │
|
||||
@@ -186,9 +186,9 @@ Scientific diagram guidelines + User request
|
||||
|
||||
**Output:** `diagram_v1.png`
|
||||
|
||||
### Quality Review by Gemini 3.1 Pro Preview
|
||||
### Quality Review by Gemini 3.6 Flash
|
||||
|
||||
Gemini 3.1 Pro Preview evaluates the diagram on:
|
||||
Gemini 3.6 Flash evaluates the diagram on:
|
||||
1. **Scientific Accuracy** (0-2 points) - Correct concepts, notation, relationships
|
||||
2. **Clarity and Readability** (0-2 points) - Easy to understand, clear hierarchy
|
||||
3. **Label Quality** (0-2 points) - Complete, readable, consistent labels
|
||||
@@ -225,10 +225,10 @@ VERDICT: ACCEPTABLE (for poster, threshold 7.0)
|
||||
### Subsequent Iterations (Only If Needed)
|
||||
|
||||
If quality is below threshold, the system:
|
||||
1. Extracts specific issues from Gemini 3.1 Pro Preview's review
|
||||
1. Extracts specific issues from Gemini 3.6 Flash's review
|
||||
2. Enhances the prompt with improvement instructions
|
||||
3. Regenerates with Nano Banana 2
|
||||
4. Reviews again with Gemini 3.1 Pro Preview
|
||||
4. Reviews again with Gemini 3.6 Flash
|
||||
5. Repeats until threshold met or max iterations reached
|
||||
|
||||
### Review Log
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/citation-management/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-26
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/citation-management/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: citation-management
|
||||
@@ -10,7 +10,7 @@ description: Comprehensive citation management for academic research. Search Goo
|
||||
allowed-tools: Read Write Edit Bash
|
||||
license: MIT License
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for LLM-powered citation steps.", "required_for": "optional features"}, {"name": "NCBI_EMAIL", "prompt": "Email for NCBI Entrez identification.", "required_for": "optional features"}, {"name": "NCBI_API_KEY", "prompt": "NCBI API key to raise Entrez rate limits.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for LLM-powered citation steps."}, {"name": "NCBI_EMAIL", "required": false, "description": "Email for NCBI Entrez identification."}, {"name": "NCBI_API_KEY", "required": false, "description": "NCBI API key to raise Entrez rate limits."}]}}
|
||||
metadata: {"version": "1.3", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for LLM-powered citation steps."}, {"name": "NCBI_EMAIL", "required": false, "description": "Email for NCBI Entrez identification."}, {"name": "NCBI_API_KEY", "required": false, "description": "NCBI API key to raise Entrez rate limits."}]}}
|
||||
---
|
||||
|
||||
# Citation Management
|
||||
|
||||
+4
-4
@@ -1,8 +1,8 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/clinical-decision-support/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-26
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/clinical-decision-support/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: clinical-decision-support
|
||||
@@ -10,7 +10,7 @@ description: Generate professional clinical decision support (CDS) documents for
|
||||
allowed-tools: Read Write Edit Bash
|
||||
license: MIT License
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# Clinical Decision Support Documents
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/hypothesis-generation/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/hypothesis-generation/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: hypothesis-generation
|
||||
@@ -10,7 +10,7 @@ description: Structured hypothesis formulation from observations. Use when you h
|
||||
allowed-tools: Read Write Edit Bash
|
||||
license: MIT license
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# Scientific Hypothesis Generation
|
||||
|
||||
@@ -1,28 +1,28 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/infographics/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/infographics/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: infographics
|
||||
description: "Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes."
|
||||
description: "Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes."
|
||||
allowed-tools: Read Write Edit Bash
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# Infographics
|
||||
|
||||
## Overview
|
||||
|
||||
Infographics are visual representations of information, data, or knowledge designed to present complex content quickly and clearly. **This skill uses Nano Banana Pro AI for infographic generation with Gemini 3 Pro quality review and Perplexity Sonar for research.**
|
||||
Infographics are visual representations of information, data, or knowledge designed to present complex content quickly and clearly. **This skill uses Nano Banana Pro AI for infographic generation with Gemini 3.6 Flash quality review and Perplexity Sonar for research.**
|
||||
|
||||
**How it works:**
|
||||
- (Optional) **Research phase**: Gather accurate facts and statistics using Perplexity Sonar
|
||||
- Describe your infographic in natural language
|
||||
- Nano Banana Pro generates publication-quality infographics automatically
|
||||
- **Gemini 3 Pro reviews quality** against document-type thresholds
|
||||
- **Gemini 3.6 Flash reviews quality** against document-type thresholds
|
||||
- **Smart iteration**: Only regenerates if quality is below threshold
|
||||
- Professional-ready output in minutes
|
||||
- No design skills required
|
||||
@@ -74,7 +74,7 @@ python skills/infographics/scripts/generate_infographic.py \
|
||||
**What happens behind the scenes:**
|
||||
1. **(Optional) Research**: Perplexity Sonar gathers accurate facts, statistics, and data
|
||||
2. **Generation 1**: Nano Banana Pro creates initial infographic following design best practices
|
||||
3. **Review 1**: **Gemini 3 Pro** evaluates quality against document-type threshold
|
||||
3. **Review 1**: **Gemini 3.6 Flash** evaluates quality against document-type threshold
|
||||
4. **Decision**: If quality >= threshold → **DONE** (no more iterations needed!)
|
||||
5. **If below threshold**: Improved prompt based on critique, regenerate
|
||||
6. **Repeat**: Until quality meets threshold OR max iterations reached
|
||||
@@ -369,7 +369,7 @@ python skills/infographics/scripts/generate_infographic.py \
|
||||
┌─────────────────────────────────────────────────────┐
|
||||
│ 1. Generate infographic with Nano Banana Pro │
|
||||
│ ↓ │
|
||||
│ 2. Review quality with Gemini 3 Pro │
|
||||
│ 2. Review quality with Gemini 3.6 Flash │
|
||||
│ ↓ │
|
||||
│ 3. Score >= threshold? │
|
||||
│ YES → DONE! (early stop) │
|
||||
@@ -381,7 +381,7 @@ python skills/infographics/scripts/generate_infographic.py \
|
||||
|
||||
### Quality Review Criteria
|
||||
|
||||
Gemini 3 Pro evaluates each infographic on:
|
||||
Gemini 3.6 Flash evaluates each infographic on:
|
||||
|
||||
1. **Visual Hierarchy & Layout** (0-2 points)
|
||||
- Clear visual hierarchy
|
||||
|
||||
@@ -1,15 +1,15 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/latex-posters/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/latex-posters/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: latex-posters
|
||||
description: "Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices for visual communication."
|
||||
allowed-tools: Read Write Edit Bash
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# LaTeX Research Posters
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/markitdown/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/markitdown/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: markitdown
|
||||
@@ -10,7 +10,7 @@ description: Convert files and office documents to Markdown. Supports PDF, DOCX,
|
||||
allowed-tools: Read Write Edit Bash
|
||||
license: MIT license
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# MarkItDown - File to Markdown Conversion
|
||||
|
||||
+4
-4
@@ -2,9 +2,9 @@
|
||||
title: "MarkItDown API Reference"
|
||||
task: ""
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/markitdown/references/api_reference.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/markitdown/references/api_reference.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
author: upstream
|
||||
@@ -260,7 +260,7 @@ result = md.convert("presentation.pptx")
|
||||
|
||||
Popular models with vision support:
|
||||
- `anthropic/claude-opus-4.5` - **Recommended for scientific vision**
|
||||
- `google/gemini-3-pro-preview` - Gemini Pro Vision
|
||||
- `google/gemini-3.6-flash` - Gemini Flash Vision
|
||||
|
||||
See https://openrouter.ai/models for the complete list.
|
||||
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/scientific-slides/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/scientific-slides/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: scientific-slides
|
||||
@@ -10,7 +10,7 @@ description: Build slide decks and presentations for research talks. Use this fo
|
||||
allowed-tools: Read Write Edit Bash
|
||||
license: MIT license
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# Scientific Slides
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/scientific-writing/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/scientific-writing/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: scientific-writing
|
||||
@@ -10,7 +10,7 @@ description: Core skill for the deep research and writing tool. Write scientific
|
||||
allowed-tools: Read Write Edit Bash
|
||||
license: MIT license
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# Scientific Writing
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
lineage_type: import
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/treatment-plans/SKILL.md
|
||||
upstream_sha: 9c9bd2e9
|
||||
imported_at: 2026-06-27
|
||||
upstream_source: https://github.com/K-Dense-AI/scientific-agent-skills/blob/831d49eb/skills/treatment-plans/SKILL.md
|
||||
upstream_sha: 831d49eb
|
||||
imported_at: 2026-07-21
|
||||
prompt_class: prompt
|
||||
upstream_changes: accepted
|
||||
name: treatment-plans
|
||||
@@ -10,7 +10,7 @@ description: Generate concise (3-4 page), focused medical treatment plans in LaT
|
||||
allowed-tools: Read Write Edit Bash
|
||||
license: MIT license
|
||||
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
|
||||
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}
|
||||
---
|
||||
|
||||
# Treatment Plan Writing
|
||||
|
||||
Reference in New Issue
Block a user