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このリポジトリの skills
SkillsMP は TuYv/ccpm から 5,252 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
TuYv/ccpm収集済み skill 5,252 件中 40 件を表示しています。
/cs:cco-review <plan> — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring. Use when gross retention is slipping, before approving CSM headcount, or when…
原文の言語: 英語
/cs:cdo-review <plan> — Decision-driven Chief Data Officer interrogation of any plan that touches training data, data architecture, data productization, or data team hiring. Use when validating training-data rights before model work, choosing warehouse vs…
原文の言語: 英語
Executive leadership guidance for strategic decision-making, organizational development, and stakeholder management. Use when planning strategy, preparing board presentations, managing investors, developing organizational culture, making executive decisions,…
原文の言語: 英語
Financial leadership for startups and scaling companies. Financial modeling, unit economics, fundraising strategy, cash management, and board financial packages. Use when building financial models, analyzing unit economics, planning fundraising, managing cash…
原文の言語: 英語
/cs:cfo-review <plan> — Numerate-skeptic interrogation of any plan that touches money. Unit economics, runway, dilution, capital allocation. Use when a plan commits meaningful spend — e.g. a hiring wave, a fundraise decision, or a new channel budget.
原文の言語: 英語
Pre-mortem plan analysis. Imagine the plan failed 12 months from now and work backwards to find the weaknesses. Surfaces assumptions, dependencies, and execution risks before committing resources. Use when before significant resource commitment, before…
原文の言語: 英語
Framework for rolling out organizational changes without chaos. Covers the ADKAR model adapted for startups, communication templates, resistance patterns, and change fatigue management. Handles process changes, org restructures, strategy pivots, and culture…
原文の言語: 英語
Produce consistent, auditable release notes from Conventional Commits. Separates commit parsing, semantic-bump logic, and changelog rendering for automated releases with editorial control. Use when cutting a release, generating CHANGELOG.md from git history,…
原文の言語: 英語
Generate changelogs from git history and validate conventional commits. Usage: /changelog <generate|lint> [options]
原文の言語: 英語
Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints. For Head of Commercial, RevOps, and…
原文の言語: 英語
Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin",…
原文の言語: 英語
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding…
原文の言語: 英語
Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named…
原文の言語: 英語
Chief Data Officer advisory for startups: AI training data rights and consent provenance, data product strategy (warehouse vs lakehouse vs mesh, build-vs-buy), B2B customer-data-as-asset valuation and M&A readiness, data team org evolution. Use when deciding…
原文の言語: 英語
C-suite orchestration layer. Routes founder questions to the right advisor role(s), triggers multi-role board meetings for complex decisions, synthesizes outputs, and tracks decisions. Every C-suite interaction starts here. Loads company context automatically.
原文の言語: 英語
People leadership for scaling companies. Hiring strategy, compensation design, org structure, culture, and retention. Use when building hiring plans, designing comp frameworks, restructuring teams, managing performance, building culture, or when user mentions…
原文の言語: 英語
Reduce voluntary and involuntary churn through cancel flow design, save offers, exit surveys, and dunning sequences. Use when designing or optimizing a cancel flow, building save offers, setting up dunning emails, or reducing failed-payment churn. Trigger…
原文の言語: 英語
Re-detect this project's tech stack from package.json / requirements.txt / pyproject.toml / go.mod / Cargo.toml and diff it against the Tech Stack section of every CLAUDE.md. Read-only — returns added / removed / renamed dependencies, never edits.
原文の言語: 英語
Audit every CLAUDE.md in this project for drift against the last week of git history. Flags sections that reference deleted files, renamed paths, or removed dependencies. Read-only — returns a punch list, never edits.
原文の言語: 英語
Verify every @path chain import and every markdown link inside every CLAUDE.md in this project resolves to an existing file. Read-only — returns broken links with file:line refs, never edits.
原文の言語: 英語
Behavioral guardrails for LLM-assisted coding. Use when writing, reviewing, or refactoring code in any project to avoid overcomplication, keep changes surgical, surface assumptions early, and execute against verifiable success criteria.
原文の言語: 英語
Analyzes, generates, and enhances CLAUDE.md files for any project type using best practices, modular architecture support, and tech stack customization. Use when setting up new projects, improving existing CLAUDE.md files, or establishing AI-assisted…
原文の言語: 英語
Interactively debug source code — set breakpoints, step through execution line by line, inspect live variable state, evaluate expressions against the running program, and navigate the call stack to trace root causes. Use when a program crashes, raises…
原文の言語: 英語
Generate web assets including favicons, app icons (PWA), and social media meta images (Open Graph) for Facebook, Twitter, WhatsApp, and LinkedIn. Use when users need icons, favicons, social sharing images, or Open Graph images from logos or text slogans.…
原文の言語: 英語
Predict protein 3D structures with AlphaFold2 via ColabFold — MMseqs2-accelerated MSAs, monomer and AlphaFold2-Multimer complex folding, and confidence-based validation (pLDDT, pTM/ipTM, PAE). Use when folding a protein sequence or complex from FASTA,…
原文の言語: 英語
Build, slice, concatenate, read, and write AnnData annotated data matrices (obs, var, X, layers, obsm, uns) — the scverse data STRUCTURE, not an analysis pipeline. Use when creating or wrangling .h5ad/zarr files, managing cell and gene annotations,…
原文の言語: 英語
Infer gene regulatory networks (GRNs) from expression matrices using arboreto's scalable GRNBoost2 and GENIE3 tree-ensemble algorithms with Dask-distributed computation. Use when analyzing bulk or single-cell RNA-seq transcriptomics to map…
原文の言語: 英語
Manipulate biological sequences, parse FASTA/GenBank/PDB files, run phylogenetics, and access NCBI/PubMed programmatically via Biopython (Bio.SeqIO, Bio.Entrez, Bio.PDB, Bio.Blast). Use when scripting custom bioinformatics pipelines, batch-processing sequence…
原文の言語: 英語
Query 40+ bioinformatics web services through one consistent Python API with bioservices (UniProt, KEGG, ChEMBL, Reactome, Ensembl, NCBI and more). Use when a workflow must hit multiple databases together, map identifiers across services, or run…
原文の言語: 英語
Runs NCBI BLAST+ 2.17.0 sequence searches from the command line: makeblastdb (with -parse_seqids), blastn/blastp/blastx/tblastn with tabular -outfmt 6/7 for parsing, correct -task choice (megablast vs blastn vs blastn-short), -taxids/-negative_taxids…
原文の言語: 英語
Co-fold biomolecular complexes with Boltz-2, an open AlphaFold3-style model — predict protein + ligand (SMILES/CCD), protein + nucleic-acid, and multi-chain structures in one pass, with binding-affinity prediction. Use when folding a protein together with a…
原文の言語: 英語
Predict genome-wide functional genomics tracks from DNA sequence with Borzoi (Linder 2025) — a sequence-to-function model outputting RNA-seq, CAGE, ATAC, and ChIP coverage across long context, used to score non-coding and regulatory variant effects. Use when…
原文の言語: 英語
Query the CZ CELLxGENE Census (61M+ cells) programmatically via cellxgene-census and TileDB-SOMA, slicing expression by tissue, disease, or cell type and returning AnnData. Use when pulling reference single-cell RNA-seq data from the largest curated public…
原文の言語: 英語
Predict biomolecular complexes with Chai-1, an open AlphaFold3-style model that folds multi-entity assemblies (proteins, ligands, nucleic acids) from a single typed FASTA — strong on antibody–antigen and protein–ligand complexes, with optional MSA and…
原文の言語: 英語
Verifies that every entry in a bibliography ACTUALLY EXISTS by cross-checking it against four keyless public scholarly APIs (Crossref, OpenAlex, Semantic Scholar, arXiv) with a polite mailto identifier, resolving DOI/arXiv IDs, fuzzy-matching title and…
原文の言語: 英語
Generates professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings — biomarker-stratified patient cohort analyses with outcomes and evidence-based treatment recommendation reports with decision algorithms,…
原文の言語: 英語
Writes comprehensive clinical reports — case reports (CARE guidelines), diagnostic reports (radiology, pathology, lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP notes, H&P, discharge summaries) — with templates, regulatory…
原文の言語: 英語
Build and analyze genome-scale constraint-based metabolic models with COBRApy — flux balance analysis (FBA), flux variability analysis (FVA), gene and reaction knockouts, flux sampling, and SBML model I/O. Use when simulating metabolic networks, predicting…
原文の言語: 英語
Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold…
原文の言語: 英語
Runs a 13-agent deep research pipeline for rigorous academic work on any topic across 7 modes (full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis), covering…
原文の言語: 英語