New skill establishing markdown + Mermaid diagrams as the default and
canonical documentation format for all scientific skill outputs.
Core principle (from K-Dense Discord, 2026-02-19): Mermaid in markdown
is the source of truth — text-based, version-controlled, token-efficient,
universally renderable. Python/AI images are downstream conversions only.
SKILL.md includes:
- Full 'source format' philosophy with three-phase workflow diagram
- 24-entry diagram type selection table with links to each guide
- 9-entry document template index
- Per-skill integration guides (scientific-schematics, scientific-writing,
literature-review, and any other output-producing skill)
- Quality checklist for finalizing documents from any skill
- Full attribution for ported Apache-2.0 content
Originated from conversation between Clayton Young (Boreal Bytes) and the
K-Dense team regarding documentation standards for shared scientific skills.
All content ported from borealBytes/opencode under Apache-2.0 license with
attribution headers prepended to each file.
- references/markdown_style_guide.md (~733 lines): full markdown formatting,
citation, collapsible sections, emoji, Mermaid integration, and template
selection guide
- references/mermaid_style_guide.md (~458 lines): full Mermaid standards —
emoji set, classDef color palette, accessibility (accTitle/accDescr),
theme neutrality (no %%{init}), and diagram type selection table
- references/diagrams/ (24 files): per-type exemplars, tips, and templates
for all Mermaid diagram types
- templates/ (9 files): PR, issue, kanban, ADR, presentation, how-to,
status report, research paper, project docs
Source: https://github.com/borealBytes/opencode
New skill for generating scientific infographics including:
- SKILL.md with comprehensive guidelines for infographic creation
- Design principles and color palette references
- Scripts for AI-powered infographic generation
- Support for various infographic types (statistical, process, comparison, etc.)
Co-authored-by: Cursor <cursoragent@cursor.com>
- Added criteria for identifying high-quality literature, emphasizing the importance of Tier-1 journals and citation counts.
- Updated guidelines for citation finding to prioritize influential papers and reputable authors.
- Revised abstract writing instructions to reflect the preference for flowing paragraphs over structured formats.
- Included best practices for generating AI schematics, specifically regarding figure numbering and content clarity.
- Replace direct calls to AllChem, Pairs, and Torsions with rdFingerprintGenerator in similarity_search.py
- Update example code in SKILL.md to reflect the new API usage
- Maintain existing functionality while adopting the modern fingerprint generation interface recommended by RDKit
- Updated SKILL.md in citation management to include best practices for identifying seminal and high-impact papers, emphasizing citation count thresholds, venue quality tiers, and author reputation indicators.
- Expanded literature review SKILL.md to prioritize high-impact papers, detailing citation metrics, journal tiers, and author reputation assessment.
- Added comprehensive evaluation strategies for paper impact and quality in literature_search_strategies.md, including citation count significance and journal impact factor guidance.
- Improved research lookup scripts to prioritize results based on citation count, venue prestige, and author reputation, enhancing the quality of research outputs.
- Add new nstc_guidelines.md with official requirements and practical insights
- Include CM03 format specifications and page limits by field
- Integrate LaTeX templates (CTAN package, Overleaf templates)
- Add practical writing strategies from three expert reviewers:
* Prof. Huang You-Ping (NPU): Scoring thresholds and section strategies
* Prof. Guo Yao-Huang: Closed-loop logic and KPI formulation
* President Wei Yao-Hui (Mackay): SMART principles and review dimensions
- Include budget preparation guidance and common pitfalls
- Update SKILL.md to reference NSTC in overview and agency list
This comprehensive guide provides 700+ lines of actionable guidance for
Taiwan NSTC (formerly MOST/NSC) research proposal writing.
- Change stream_name to stream_id in read_spikeglx() call
- Change output_folder to folder in run_sorter() call
These parameters were renamed in SpikeInterface ≥0.100.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Adds comprehensive toolkit for analyzing Neuropixels high-density neural
recordings using SpikeInterface, Allen Institute, and IBL best practices.
Features:
- Data loading from SpikeGLX, Open Ephys, and NWB formats
- Preprocessing pipelines (filtering, phase shift, CAR, bad channel detection)
- Motion/drift estimation and correction
- Spike sorting integration (Kilosort4, SpykingCircus2, Mountainsort5)
- Quality metrics computation (SNR, ISI violations, presence ratio)
- Automated curation using Allen/IBL criteria
- AI-assisted visual curation for uncertain units
- Export to Phy and NWB formats
Supports Neuropixels 1.0 and 2.0 probes.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add comprehensive BRENDA database skill with API integration
- Include enzyme data retrieval, pathway analysis, and visualization
- Support for enzyme queries, kinetic parameters, and taxonomy data
- Add visualization scripts for enzyme pathways and kinetics
