superpowers
claudecodexCore skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
15 skills · hooks
科研循环参考骨架 + 生物医学治理层
Plugin bio-loop from marketplace lab-marketplace in HERRY423/AI-BioResearch-Workflow. Commands read from the repo's manifest — 1 month ago.
This plugin runs code on your machine — it starts local MCP servers. The exact commands are listed below; read them before installing.
claim-verification把一份分析报告、手稿草稿或结论段落拆成原子陈述,逐条打到权威数据库与文献核验,并标注每条的支持/反驳/无证据状态。当用户要求核查结论、验证结果、检查引用是否属实、审阅手稿的事实性、或问"这些数字可靠吗"时使用。也在提交前的最后一道自查时使用。
controlled-data-protocol处理受控访问的人类数据(dbGaP、All of Us、UK Biobank、EGA、TCGA controlled)时的合规操作规程。当用户提到这些数据源、提到 TRE/RAP/Workbench、问"能不能用 AI 分析患者数据"、需要申请数据访问、或需要把分析提交进安全计算环境时使用。
deterministic-pipeline把一个分析需求写成可复现的 Nextflow 或 Snakemake 工作流,含测试、容器 digest 固定、参考版本固定、provenance 输出。当用户要求做 RNA-seq/WGS/WES/ATAC-seq/单细胞分析、跑 nf-core 流程、批量处理测序数据、或需要"可复现的分析流程"时使用。也在需要把一段探索性 notebook 固化成生产流程时使用。
kg-hypothesis从生物医学知识图谱生成可检验假设。当用户要求提出研究假设、寻找机制解释、做靶点发现、药物重定位、或问"X 和 Y 之间可能有什么联系"时使用。也在需要为一个观察到的表型找候选通路时使用。
pubmedconnects to: https://pubmed.mcp.claude.com/mcp
biorxivconnects to: https://hcls.mcp.claude.com/biorxiv/mcp
c-trialsconnects to: https://hcls.mcp.claude.com/clinical_trials/mcp
chemblconnects to: https://hcls.mcp.claude.com/chembl/mcp
otconnects to: https://mcp.platform.opentargets.org/mcp
synapseconnects to: https://mcp.synapse.org/mcp
consensusconnects to: https://mcp.consensus.app/mcp
biorenderconnects to: https://mcp.services.biorender.com/mcp
kgconnects to: http://localhost:8765/mcp
kg-stdioruns: python -m bridge.kg_mcp_server
biomniruns: python -m bridge.biomni_mcp_server
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
15 skills · hooks
HADS (Human-AI Document Standard) — semantic tagging convention for docs that work for both humans and AI models — plus the grounded-vault pattern for provenance-linked, drift-checked knowledge stores.
2 skills
Evidence-backed BioPharma research workflows over Maven Bio's drug, trial, company, and deal knowledge graph. Skills for competitive pipelines, indication landscapes, asset profiles, deal and financing activity, and evidence synthesis grounded in FDA, SEC, clinical, and press sources. Requires a Maven Bio account.
16 skills · 1 agent · 1 MCP server
Study companion for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org. Twenty chapter files, a glossary, patterns and a cheatsheet index the whole book, and a delta reference dates it against 2026 practice with per-claim confidence levels: double descent qualifying the U-curve, AdamW splitting weight decay from L2, transformers displacing Chapter 10's recurrence, diffusion growing out of Chapter 18's score matching. Four stdlib tools make it executable — a prerequisite-closed reading-path planner that refuses goals the book does not cover, a training diagnostic running Chapter 11's rules in priority order so a NaN is never reported as overfitting, a capacity planner that ranks 'shrink the model' last when overparameterized, and a parameter/FLOP/activation-memory calculator that refuses a stack whose shapes do not connect. A companion, not a compilation: the book is copyrighted, so nothing here reproduces its text.
1 skill · 3 commands · 1 agent
Remove multi-vendor AI provenance marks from text, images, documents, and media. Bundles the remove-ai-marks and clean-user-facing-text skills.
2 skills · hooks
Comprehensive context engineering and harness engineering skills for production-grade AI agent systems: fundamentals, degradation patterns, compression, optimization, self-managed context (model-controlled live context editing), multi-agent coordination, long-horizon prompting (pseudo-formal task briefs for long-running and parallel agents), memory systems, tool design, filesystem context, hosted agents, evaluation, autonomous harnesses, self-improvement loops (RSI, meta-harnesses, evolutionary scaffold search), latent briefing (KV cache sharing between agents), project development, and cognitive architecture. Ships with a researcher operating system (rubrics, mechanism registry, claim provenance, run state machine, adversarial benchmarks, continuous loop).
19 skills
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