'experiment' 검색 결과

Treats a ctDNA assay as a molecule-counting experiment at the Poisson edge and builds its analytical-validation case the measurement-science way. Covers the genome-equivalent currency (~330 haploid copies/ng), the lambda = input_GE x VAF sampling ceiling (lambda>=3 for ~95% detection), the error-suppression ladder (raw NGS ~1e-3 -> single-strand UMI ~1e-4/1e-5 -> duplex <1e-7), the CLSI EP17 LoB/LoD/LoD95/LoQ framework, the per-locus-vs-panel-integrated LoD distinction that lets bespoke MRD reach ppm, contrived/SEQC2 reference standards, and honest LoD reporting conditioned on input mass + consensus depth + replicate detection rate. Use when stating or trusting a sensitivity claim, designing a dilution-series validation, deciding how many genome equivalents are needed at a target VAF, choosing a single-locus vs panel-integrated LoD, or auditing a "detects 0.1% VAF" claim.

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End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.

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Experimental behavioral evaluator. Drives a running artifact via browser/curl/CLI and records rubric evidence; the runner is not yet a fully implemented automated evaluation system.

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Experimental/manual harness canary procedure. It records benchmark manifests and scores but does not provide a fully automated runner.

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Experimental/manual harness canary procedure. It records benchmark manifests and scores but does not provide a fully automated runner.

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Experimental behavioral evaluator. Drives a running artifact via browser/curl/CLI and records rubric evidence; the runner is not yet a fully implemented automated evaluation system.

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Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

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Plan vulnerability research using conventional bug-hunting and pentest stage names, specialty playbooks, and a research-hypothesis-experiment loop. Use when designing a bug bounty workflow, selecting tools and strategies, building a decision tree, or turning a target/scope into a staged hunting plan.

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Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

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Implement tasks from an OpenSpec change (Experimental)

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Archive a completed change in the experimental workflow

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EXPERIMENTAL. Join or leave an org-team coordination channel as a session peer. `/companion on <channel_id> [peer_id]` registers this Claude Code session as a `pclass:"session"` peer and works the claim → execute → signal loop, escalating un-decidable forks to the lead (never deciding). `/companion off` deregisters. `/companion status` reports the current peer. Part of org mode (Article X), which is opt-in via `velocity.org_mode.enabled` and OFF by default. Use when a human launches a second session to act as a peer alongside a lead.

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W&B: log ML experiments, sweeps, model registry, dashboards.

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Throwaway experiments to validate an idea before build.

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Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.

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Diagnose an uncertain bug by designing experiments that distinguish competing causes, especially speculative cache, timing, environment, or concurrency explanations.

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Generates an experiment-overview snapshot of all research questions under research/reports/. Invoke when a new point-in-time report across all RQs should be produced.

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Expert-level statistics knowledge. Use when working with probability distributions, hypothesis testing, regression, Bayesian statistics, statistical inference, experimental design, ANOVA, or statistical modeling. Also use when the user mentions 'p-value', 'confidence interval', 'hypothesis test', 'regression', 'ANOVA', 'chi-square', 't-test', 'Bayesian', 'maximum likelihood', 'statistical significance', 'correlation', 'normal distribution', or 'sampling distribution'.

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Orchestrate an end-to-end data analysis or machine learning project from decision framing through reproducible handoff. Use when a request spans multiple lifecycle stages or an ambiguous modeling request must become a decision-ready result; use narrower audit or experiment-design skills for isolated reviews.

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Prices research, tests, surveys, dashboards and experiments before running them, by computing how much the result would raise expected utility - which is zero whenever no outcome would change the decision. Use when someone proposes an A/B test, user survey, market study, competitor analysis, analytics build, consultant, pilot, or "let's gather more data", and when deciding how large a study needs to be.

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Use to drive a scalar metric down or up across bounded iterations — keep on strict improvement, revert otherwise, state on disk. Triggers 'minimize X', 'optimize until it stops improving'.

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kpopper Hub: optional experimental application for exploring the project record. Use when the user explicitly requests kpopper Hub or its record page, its graph, layout or verification, or has a standing preference for this application. Do not render automatically after mapping or recording. Install the HTML runtime before use. Not for ordinary HTML documents or a text answer from the record. Requests come in any language.

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Annotated Documents: optional experimental application for standalone HTML with evidence. Use when the user explicitly requests Annotated Documents or a kpopper HTML document with evidence, refreshes an existing kpopper document, or has a standing preference for this application. Generic HTML requests do not select it. Install the HTML runtime before use. Not for the record's own page or an ordinary website. Requests come in any language.

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Quando o usuário quer criar ou otimizar paywalls in-app, telas de upgrade, modais de upsell ou feature gates. Use também quando o usuário mencionar "paywall", "tela de upgrade", "modal de upgrade", "upsell", "feature gate", "converter free para paid", "conversão freemium", "tela de expiração de trial", "tela de limite atingido", "prompt de upgrade de plano" ou "preço in-app". Distinto de páginas de preço públicas (veja page-cro) — esta skill foca em momentos de upgrade in-product onde o usuário já experimentou valor.

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