Product & Planning

tomevault-io Bundle

Comprehensive meta-skill for discovering and orchestrating ALL available tools, MCP servers, skills, plugins, agents, and CLI capabilities to solve any problem optimally. Invoke this skill for ANY non-trivial task — building software, researching topics, analyzing data, debugging systems, deploying code, creating reports, automating workflows, or solving complex multi-step problems. This skill teaches runtime capability discovery via ToolSearch, parallel agent dispatch, and multi-tool orchestration across Firecrawl (web research), Playwright (browser automation), Pinecone (vector storage/RAG), Vercel (deployment), Cloudflare (edge infrastructure), Mermaid Chart (diagrams), Context7 (library docs), Greptile (codebase search), HuggingFace (ML/AI), CodeRabbit (code review), GerdsenAI Document Builder (PDF reports), language servers (TypeScript, Python, C#, C++), and the superpowers workflow skills (TDD, debugging, planning, code review, worktrees). Even for seemingly simple tasks, run capability discovery first

tomevault-io Bundle

Map requirements (PRD/user stories/AC) to comprehensive test coverage using a traceability matrix (RTM). Outputs coverage gaps, risks, test levels, prioritization, automation candidates, and change-impact notes. Designed for QA/Test Architect workflows. Use when this capability is needed.

tomevault-io Bundle

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tomevault-io Bundle

Environment manager-specific discovery patterns and known issues. Use when working on or reviewing environment discovery code for conda, poetry, pipenv, pyenv, or venv. Use when this capability is needed.

tomevault-io Bundle

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery. Use when this capability is needed.

tomevault-io Bundle

Python network device discovery, scanning, and HTTP API management. Covers raw UDP sockets, vendor broadcast protocols (GBL reference), subnet scanning, HTTPS fallback, interface enumeration, and parallel probing. Built from production deployment to 120+ devices. Use when this capability is needed.

tomevault-io Bundle

Accept a GitHub issue URL or issue details, create a comprehensive plan (in plan mode - shows plan first), then implement the solution including tests and documentation, create/update release notes for Home Assistant users, and update the README roadmap for new features. Use when the user provides a GitHub issue or asks to solve an issue. ALWAYS presents the plan first and waits for user approval before implementing. Use when this capability is needed.

tomevault-io Bundle

Comprehensive toolkit for product managers including RICE prioritization, customer discovery, PRD templates, metrics frameworks, and go-to-market strategies. Use when prioritizing features, conducting customer research, defining requirements, or tracking product success. Use when this capability is needed.

tomevault-io Bundle

Azure API Center SDK for .NET. Centralized API inventory management with governance, versioning, and discovery. Use when this capability is needed.

tomevault-io Bundle

Implements nested cross-validation and stratified splits for unbiased model evaluation on biomedical datasets. Prevents data leakage and overfitting in biomarker discovery. Use when validating classifiers or optimizing hyperparameters on omics data. Use when this capability is needed.

tomevault-io Bundle

Selects informative features for biomarker discovery using Boruta all-relevant selection, mRMR minimum redundancy, and LASSO regularization. Use when identifying biomarkers from high-dimensional omics data. Use when this capability is needed.

tomevault-io Bundle

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery. Use when this capability is needed.

javimosch Skill

pppoe-discovery Plugin

holobiomicslab Skill

Use when when you have raw LC-MS chromatographic data (mzML or vendor format) and need to identify and characterize all detectable peaks across the full retention time range for untargeted metabolomics or discovery workflows.

holobiomicslab Skill

Use when you have GC–MS data from human breath samples and need to identify marker metabolites for disease diagnosis, phenotyping, or biomarker discovery without a predefined target list. Your data is noisy or conventional peak picking has produced high false-positive rates.

holobiomicslab Skill

Use when after running QC analysis on NMR or MS metabolomic data and obtaining per-feature CV values, use this skill to validate that the dataset meets FDA thresholds (CV < 0.30 for discovery, CV < 0.15 for quantification) and to report the proportion of features meeting each threshold.

holobiomicslab Skill

Use when processing IM-MS data files (Agilent .d or UIMF format) that contain high-abundance ions suspected of signal saturation, particularly in untargeted or discovery proteomics/metabolomics workflows where dynamic range compression would obscure quantitative relationships.

holobiomicslab Skill

Use when you have completed NMR data quality control analysis and possess per-feature CV values, and you need to formally assess whether the metabolomic dataset meets FDA regulatory standards for downstream biomarker discovery or quantitative assays.

holobiomicslab Skill

Use when you have mass spectrometry imaging (MSI) data with ion images that need low-dimensional representation learning for downstream tasks like co-localized ion searching or isotope discovery.

diegosouzapw Bundle

CodeNavi workflow skill. Use this skill when the user needs Your pathfinder for navigating unknown codebases. Investigates with precision, implements surgically, and never assumes \u2014 if it doesn't know, it says so. Maintains a .notebook/ knowledge base that grows across sessions, turning every discovery into lasting intelligence. Summons available skills, MCPs, and docs when the mission demands. Use when fixing bugs, implementing features, refactoring, investigating flows, or any development task in unfamiliar territory. Triggers on "fix this", "implement this", "how does this work", "investigate this flow", "help me with this code". Do NOT use for greenfield scaffolding, CI/CD, or infrastructure provisioning and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

diegosouzapw Bundle

RFC Creator workflow skill. Use this skill when the user needs Creates structured Request for Comments (RFC) documents for proposing and deciding on significant changes. Use when the user says "write an RFC", "create a proposal", "I need to propose a change", "draft an RFC", "document a decision", or needs stakeholder alignment before making a major technical or process decision. Do NOT use for TDDs/implementation docs (use technical-design-doc-creator instead), README files, or general documentation and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

diegosouzapw Bundle

exa-search workflow skill. Use this skill when the user needs Semantic search, similar content discovery, and structured research using Exa API. Use when you need semantic/embeddings-based search, finding similar content, or searching by category (company, people, research papers, etc.) and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

diegosouzapw Bundle

Filesystem-Based Context Engineering workflow skill. Use this skill when the user needs Use for file-based context management, dynamic context discovery, and reducing context window bloat. Offload context to files for just-in-time loading and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

diegosouzapw Bundle

Frontend Blueprint workflow skill. Use this skill when the user needs AI frontend specialist and design consultant that guides users through a structured discovery process before generating any code. Collects visual references, design tokens, typography, icons, layout preferences, and brand guidelines to ensure the final output matches the user's vision with high fidelity. Use when the user asks to build, design, create, or improve any frontend interface \u2014 websites, landing pages, dashboards, components, apps, emails, forms, modals, or any UI element. Also triggers on "build me a UI", "design a page", "create a component", "improve this layout", "make this look better", "frontend", "interface", "redesign", or when the user provides mockups, screenshots, or design references. Do NOT use for backend logic, API design, database schemas, or non-visual code tasks and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

diegosouzapw Bundle

Use when you need authorized web fuzzing with ffuf for content discovery, endpoint enumeration, virtual host or parameter fuzzing, response filtering, and structured result capture while preserving upstream workflow intent, copied support files, and provenance before review, merge, or handoff.

diegosouzapw Bundle

Modular Decomposition workflow skill. Use this skill when the user needs Runs a sequenced monolith-to-modular pipeline that sizes and inventories components, finds shared domain duplication, addresses flattening and hierarchy issues, analyzes coupling, then groups components into candidate domain-aligned units, with optional embedded DDD strategic analysis for bounded contexts. Use when asking how to split a monolith, size components before extraction, find duplicated domain logic, clean up module hierarchy, measure coupling between modules, or group components into services. Do NOT use for phased extraction roadmaps or prioritization without the prior analysis steps (use decomposition-planning-roadmap after this pipeline), end-to-end legacy migration strategy writeups (use legacy-migration-planner), pure infrastructure capacity sizing, or when you only need DDD without the structural pipeline (install domain-analysis standalone) and the operator should preserve the upstream workflow, copied support files, an

holobiomicslab Skill

Use when when you have raw untargeted LC-MS metabolomics data and need to detect low-quality or mis-integrated peaks in an XCMS-processed xcmsSet object before performing metabolite annotation, statistical analysis, or biomarker discovery.

holobiomicslab Skill

Use when you have MSMS spectra from two or more compounds and need to identify which are structurally related. Use this skill when you want to rank spectrum pairs by similarity to discover novel analogs or validate structural assignments in untargeted metabolomics or natural products discovery.

holobiomicslab Skill

Use when you have per-feature CV values from quality control analysis of NMR or MS metabolomic data and need to: (1) establish whether your dataset meets FDA reproducibility standards for downstream biomarker discovery or quantification; (2) benchmark data quality against regulatory thresholds;

holobiomicslab Skill

Use when when you have preprocessed mass spectrometry imaging (MSI) ion images and need to generate augmented image pairs for contrastive learning in co-localized ion discovery tasks.

holobiomicslab Skill

Use when when you have preprocessed mass spectrometry ion images (single-channel 2D arrays or multi-channel spectral images) and need to train a self-supervised encoder to learn low-dimensional representations for downstream tasks such as co-localized ion discovery (COL mode) or isotope ion.

holobiomicslab Skill

Use when you have imaging mass spectrometry data from spatial metabolomics experiments and need to reduce the high-dimensional peak space to a ranked set of marker ions for downstream spatial analysis (e.g., tissue region annotation or biomarker discovery).

holobiomicslab Skill

Use when you have untargeted metabolomics data (e.g., LC-MS/MS spectra) and need to organize compounds by structural relatedness to enable structure discovery for unknown metabolites.

diegosouzapw Bundle

Decomposition Planning and Roadmap workflow skill. Use this skill when the user needs Creates step-by-step decomposition plans and migration roadmaps for breaking apart monolithic applications. Use when asking "what order should I extract services?", "plan my migration", "create a decomposition roadmap", "prioritize what to split", "monolith to microservices strategy", or tracking decomposition progress. Do NOT use for domain analysis (use domain-analysis) or component sizing (use component-identification-sizing) and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

thomasmoreai Skill

Expert India Digital Personal Data Protection Act, 2023 (DPDPA) compliance advisor. Use this skill whenever a user asks about the DPDPA, DPDP Act, DPDP Rules 2025, India data privacy law, Data Fiduciary obligations, Data Principal rights, Significant Data Fiduciary, Data Protection Board of India, consent under DPDPA, notice requirements, breach notification India, children's data India, cross-border data transfer India, India privacy compliance, DPDPA gap analysis, DPDPA vs GDPR, or any obligation under India's personal data protection framework. Also trigger for: "Section 6 consent", "Section 7 legitimate uses", "Section 9 children's data", "Section 10 SDF", "Section 16 cross-border", "Rule 6 breach notification", "Rule 13 SDF obligations", "Data Protection Board complaint", "verifiable parental consent India", "DPDPA compliance roadmap", or "India privacy law global company".

thomasmoreai Skill

Drafts stipulated ESI protocols for federal e-discovery. Produces court-ready agreements governing preservation, collection, processing, review, and production of electronically stored information under FRCP Rules 26, 34, 37 and Sedona Principles. Trigger when formalizing ESI procedures between parties during the discovery phase.