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Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda scheduling, soft-core potentials, MBAR/BAR analysis, cycle-closure validation, and protocol-appropriate enhanced sampling. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.

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Cross-method decision tree for calling hits in pooled CRISPR screens. Catalogs statistical models (MAGeCK RRA, MAGeCK MLE, BAGEL2, drugZ, JACKS, Chronos, CERES), experimental designs each is built for, failure modes outside design domain, reconciliation when methods disagree, multiple-testing and effect-size thresholds, the order of operations (count -> QC -> CN-correct -> hit-call -> validate), the second-best-sgRNA conservative rule, and consensus-hit strategy. Use when choosing among MAGeCK / BAGEL2 / drugZ / JACKS / Chronos for a given design, reconciling disagreement across two or three methods on the same screen, deciding whether to require consensus, gating downstream validation by hit-confidence tier, or interpreting unstable hit lists across reruns.

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Designs and analyzes combinatorial CRISPR screens covering paired-Cas9 (Big Papi, Najm 2018), enhanced AsCas12a multiplex (enCas12a, DeWeirdt 2021), in4mer 4-guide-array Cas12a (Esmaeili Anvar N et al 2024 Nat Commun 15:3577) and the Inzolia paralog-pair library, paralog-buffering detection (Dede 2020 Genome Biol; Thompson 2021 Nat Commun 12:1302), genetic-interaction (GI) scoring as observed_double_LFC minus expected_additive_double_LFC, synthetic-lethal and synthetic-rescue interaction interpretation, the half-of-essentiality buffered by paralogs phenomenon, multiplex screen statistical analysis with MAGeCK MLE interaction terms, and the relationship to single-cell combinatorial Perturb-seq. Use when designing a paralog or pathway-pair screen, choosing between paired-Cas9 (Big Papi) and Cas12a multiplex (Inzolia), interpreting genetic interaction scores, identifying synthetic-lethal targets for drug development, or scaling beyond single-gene CRISPR screens.

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Build and analyze pangenomes for prokaryotes (Panaroo, PPanGGOLiN, PEPPAN, GET_HOMOLOGUES, anvi'o pangenomics) and eukaryotes (Minigraph-Cactus, PGGB, vg pangenome graphs). Implement Tettelin core/accessory/cloud genome decomposition (Tettelin 2005), Heap's law open/closed pangenome modeling, gene presence/absence GWAS (Scoary, pyseer), pangenome graph variant calling (vg, PanGenie), and structural-variation graph indexing. Use when assembling species- or genus-level pan-gene catalogs, separating core from accessory/shell/cloud genes, testing gene-content associations with phenotypes, building pangenome graphs from haplotype-resolved assemblies, calling SVs from pangenome graphs, or selecting between bacterial-pangenome and eukaryotic-pangenome workflows.

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Run remote BLAST searches against NCBI servers using Biopython Bio.Blast.NCBIWWW. Use when identifying unknown sequences, finding homologs, picking the correct BLAST program (blastn/blastp/blastx/tblastn/tblastx/psiblast/megablast/dc-megablast), interpreting Karlin-Altschul E-values, avoiding the max_target_seqs trap (Shah 2019), choosing composition-based statistics, or limiting searches by organism. Covers RID lifecycle, database choice (nt/nr/refseq_select/swissprot), word-size and CBS taxonomy.

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Queries gnomAD v4 (807k samples), v3, v2.1.1, and constraint metrics with grpmax FAF95, bottleneck-group exclusion, LOEUF interpretation, SV/CNV/mtDNA catalogs, and Whiffin max-credible-AF framework. Use when filtering rare variants, applying ACMG BS1/BA1, ranking genes by LoF intolerance, or selecting between v2 (GRCh37 + chrX/Y constraint) and v4 (GRCh38 + 807k samples).

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This skill suggests targeted therapies (somatostatin analogs or tyrosine kinase inhibitors) to treat ectopic ACTH syndrome when ectopic ACTH secretion is confirmed or strongly suspected. Use when triggers include occult or metastatic ectopic ACTH secretion, very severe ACTH‑dependent disease uncontrolled by medical therapy, or when surgery is not possible or noncurative.

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Use for read-first Amazon Sponsored Products optimization, product-aware growth, preflight readiness, and post-change monitoring reviews that can run standalone from static exports or use Rocketcart MCP as an optional Amazon Ads plus product-intelligence layer. Guides Codex to inspect Rocketcart profiles, live SP campaigns, product ads/ASIN context, category rank/BSR movement, competitor signals, product readiness, budget and targeting drift, snapshots/changelogs, and proposed approval-gated action rows without executing writes by default.

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Start the Wasp dev server and set up full debugging visibility. This includes running the server (with access to logs), and connecting browser console access so the agent can see client-side errors. Essential for any development or debugging work.

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Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.

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YouTube transcripts to summaries, threads, blogs.

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Diagnoses failing GitHub Actions runs by reading logs, identifying the root cause, and suggesting fixes. Use this skill whenever a user shares a GHA run URL, pastes runner log output, mentions a failing workflow, asks why a CI job is broken, or says anything like "my GHA is failing", "workflow failed", "can you check my run", or "CI is broken". Also trigger when raw log text is detected in the conversation that appears to come from a GitHub Actions runner. Do NOT use for general GHA workflow authoring questions, YAML formatting help, or passing runs with no failure context.

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Answer questions about the Paseo product and app, including setup, configuration, connectivity, providers, workspaces, updates, logs, and troubleshooting. Use when a user inside Paseo asks how Paseo works, how to configure it, or why something is broken; use the paseo skill instead to operate agents and workspaces through MCP or the CLI.

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Dashboard d'avancement des epics en cours. Thin wrapper sur les scripts bash qui agrègent les logs per-agent (.claude/state/epic_run/) et le state GitHub. Pas de LLM lourd. Usage: /report [<epic_N> ...]

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Read-only SRE checkup of any GCP project: deterministic probes of the edge, Cloud Run services, 7-day error logs, Cloud Scheduler, alert policies and uptime checks, Secret Manager and IAM, the data stores and the machine's own scheduled jobs, audited into one fixed status table (LIVE / WARNING / RED / INCONCLUSIVE) with evidence, findings by severity, what could not be checked, and a single OVERALL line delivered as one notification. Parametrised by a per-project manifest, so the same routine runs on every project. Use when the operator says "cloud checkup", "SRE check", "is everything live", "what's healthy / warning / red", "any errors this week", "audit the infra", "weekly checkup", "set up the weekly checkup", before a deploy or demo, or after an incident. Cloud Run first; App Engine and GKE differ only in the serving probes.

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Use when working with Grafana — dashboards, Loki LogQL queries, alerting rules, monitoring panels — even when the user just says 'build me a dashboard' or 'query the logs' without naming Grafana.

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This skill should be used when designing terminal user interfaces, creating TUI layouts, choosing TUI color schemes, implementing keyboard navigation, building terminal dashboards, or working with any TUI framework. Activates on mentions of TUI design, terminal UI, Ratatui layout, Ink components, Textual widgets, Bubbletea views, terminal color palette, keybinding design, panel layout, split panes, terminal dashboard, box-drawing characters, sparklines, progress bars, modal dialogs, focus management, or terminal accessibility.

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Cria automaticamente changelogs voltados para usuários a partir de commits do git, analisando o histórico de commits, categorizando mudanças e transformando commits técnicos em notas de lançamento claras e amigáveis para clientes. Transforma horas de escrita manual de changelog em minutos de geração automatizada.

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CLI do Datadog para buscar logs, consultar métricas, rastrear requisições e gerenciar dashboards. Use isso ao depurar problemas em produção ou trabalhar com observabilidade do Datadog.

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Write minimal, accessible web UI without over-engineering, adapting to whatever stack the project uses — React, Vue, Svelte, Angular, web components, or plain HTML. Use this skill on every project and every task that writes or reviews markup or components, builds forms, adds interactive elements like buttons, dialogs, accordions, or tabs, or audits code for accessibility — even when the user never mentions accessibility, and even inside a framework, CMS, or design system. It's non-negotiable regardless of project type, stack, or deadline. About to reach for ARIA attributes, a dialog library, a focus-trap package, or a headless UI component? Use this skill first.

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[Implementation] Use when you need to analyze and fix issues [INTELLIGENT ROUTING]. Flag: --target={ci|issue|logs|test|types|ui} scopes the fix; --target=types resolves TypeScript errors inline.

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[Project Management] Use when you need to capture ideas, manage product backlogs, apply prioritization frameworks (RICE, MoSCoW), and facilitate stakeholder communication.

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OCM/OpenClaw envs: create, clone, upgrade, runtimes, services, logs, cleanup.

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Chooses ecosystem-native release and changelog tooling (Changesets, Melos, release-plz) plus binary distribution (GitHub Release tarballs, install.sh) when the product is an executable. Use for release CI, install.sh, versioning, CHANGELOGs, shipping MCP/CLI without clone, or meta repos that only ship skills via npx skills—not domain app tutorials.

日本語の概要は準備中です。原文の説明を表示しています。