341 件 ・ 関連度順
概要と使いどころ
Rapidly maps the evidence landscape around a medical topic by organizing major research streams, target populations, endpoints, methods, evidence density, and thin areas. Use this skill BEFORE medical-research-gap-finder — it provides the structured landscape that makes formal gap analysis more rigorous. Do not use for formal gap identification, study design, or protocol planning directly.
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Writes Specific Aims pages for grant applications. Use when drafting or revising the Specific Aims page (NIH R01/R21/R03), NSF Project Summary, or equivalent for any major funding agency. Also triggers on "write my specific aims", "help me draft specific aims for NIH", "what should a specific aims page include", "NSF project summary", "write my grant aims", or "how do I structure an R01".
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Builds prioritized manuscript revision plans for major or minor revisions by separating comments that require experiments, analyses, clarification, restructuring, or wording changes.
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Use when evaluating Paul Tudor Jones-style macro trend trades: major turning points, trend confirmation, risk control, stop discipline, liquidity, and not losing big.
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Download flood stage thresholds from NWS (National Weather Service). Use when determining flood levels for USGS stations, accessing action/minor/moderate/major flood stages, or matching stations to their flood thresholds.
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Use when completing tasks, implementing major features, or before merging to verify work meets requirements.
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Review candidate learnings in Claude Code's native auto memory (`~/.claude/projects/<project>/memory/`, machine-local) and run them through a five-critic council in parallel: generality, staleness, redundancy, evidence, format. Majority vote (3+ of 5) promotes the entry to MEMORY.md. Use when user says "promote memory", "review my learnings", "what should graduate to MEMORY.md", "five-critic council", or as monthly memory maintenance.
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Performs a structured five-stage code review covering requirements compliance, correctness, code quality, testing, and security/performance. Each stage uses targeted checklists and categorized feedback (Blocker/Major/Minor/Nit) with actionable suggestions and rationale. Use when the user asks for code review, PR feedback, pull request review, or wants their code checked for bugs, style issues, or vulnerabilities — triggered by phrases like "review my code", "check this PR", "review my changes", "pull request review", or "code feedback".
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Recover the first public timestamp and canonical major coverage for a newsjacking signal, then decide whether newer coverage is the same story, a different story, or a materially new development.
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Help a student and family plan university applications after the 高考 (gaokao): use the student's provincial rank rather than raw score, build a 冲 / 稳 / 保 (reach, match, safe) list from official historical admission data, check subject requirements under the new gaokao, and weigh major against university. Use when asked 帮我填高考志愿, 志愿怎么填, 冲稳保怎么排, 这个分数能上什么学校, or plan gaokao applications. Produces a structured application list with the reasoning for each choice, a risk check of the whole list, and the questions to settle as a family. Never guarantees admission.
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Write a fundraising case for support that makes donors want to give. Use when asked to write a case for support, a fundraising case statement, a major-gift or campaign case, or the core argument for a donation appeal. Produces a persuasive case — the need, your solution and why you, the impact a gift makes, specific funding opportunities with amounts, and a clear ask — donor-centred, not org-centred.
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Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
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Incrementally upgrade React Native Storybook across the supported migration paths. Use when upgrading `@storybook/react-native` projects from 5.3.x to 6.5.x, 6.5.x to 7.6.x, 7.6.x to 8.3.x, 8.x to 9.x, or 9.x to 10.x. Detect the currently installed Storybook version, choose only the next migration step, update dependencies and config, regenerate `storybook.requires`, convert remaining `storiesOf` stories to CSF during the `6.5.x -> 7.6.x` upgrade, and stop after a single version hop instead of jumping multiple major versions at once.
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Use when responding to Advanced Materials reviewer reports and an editor's decision — major or minor revision, or a rejection with a resubmission or transfer path. Structures the response and the manuscript changes; does not perform the underlying new experiments.
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Provider reference for collecting public profiles, posts, comments, transcripts, trends, and ad-library data from major social platforms through ScrapeCreators. Use as a dependency of research workflows, not as the final user-facing deliverable.
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Designs and analyzes pooled prime-editor (PE) screens for installing precise genetic variants without bystander confounding. Covers pegRNA design with PRIDICT and PRIDICT2 for predicting per-pegRNA editing efficiency, pegRNA architecture (spacer + scaffold + PBS + RTT), PE2/PE3/PE3b/PEmax variants, MOSAIC in situ saturation mutagenesis, the PRIME pooled-screen methodology (Ren 2023; ~3,699 ClinVar variant screens), chromatin context as a major locus-level determinant of PE efficiency, scaffold-incorporation and indel byproduct quantification with CRISPResso2, and the cross-modal validation strategy of PE + base-editor screens for variant function. Use when designing a pegRNA library for variant installation, choosing between BE and PE for a specific edit, predicting pegRNA efficiency before library synthesis, analyzing PE screen output, distinguishing intended-edit from scaffold-incorporation, or scaling PE screens to thousands of variants.
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Infer integer allele-specific copy number, tumor purity, and ploidy from tumor sequencing by jointly modeling read depth (logR) and B-allele frequency (BAF) with ASCAT, Sequenza, FACETS, PURPLE, and PureCN (tumor-only). Covers the purity-ploidy identifiability problem, the diploid-baseline (dipLogR) anchor, major/minor copy number, loss of heterozygosity, sunrise/contour fit diagnostics, and reconciliation of conflicting fits. Use when tumor analysis needs absolute copy number rather than relative log2, when estimating purity and ploidy, calling LOH or copy-neutral LOH, resolving whole-genome doubling, running tumor-only allele-specific calling, or choosing among ASCAT, Sequenza, FACETS, and PureCN.
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Build a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule overlap. Use when generating a stable peak coordinate system for downstream differential accessibility, ML feature engineering, cross-sample comparison, or fixed-width peak counts; covers Corces 2018 iterative overlap (501 bp), DiffBind summit re-centering, and ENCODE consistency rules.
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5 expert personas debate proposed changes before implementation. Catches architectural, security, performance, and UX issues early. Use before major features or risky changes.
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E-commerce warehouse and inventory optimization advisor. Analyzes inventory health, calculates safety stock and reorder points, performs ABC analysis, evaluates fulfillment costs, and provides actionable recommendations for improving efficiency. Supports all major fulfillment models: Self-fulfillment, Amazon FBA/FBM, Walmart WFS, 3PL, Shopify Fulfillment, TikTok Shop, Dropshipping, and Hybrid setups. No API key required. Use when: (1) reducing stockouts or overstock, (2) calculating safety stock levels, (3) optimizing warehouse costs, (4) improving Amazon IPI score, (5) analyzing inventory KPIs.
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Choose and apply the correct semantic version bump for this repository. Use for every user-visible release, before merge when a change set should ship as patch, minor, or major, and whenever package/plugin/desktop version metadata must stay synchronized.
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Probes each major Agent Monitor API route — /api/stats, /api/analytics, /api/sessions, /api/pricing/cost, /api/workflows/runs, /api/cc-config/overview — and reports each one's HTTP status, latency, and response shape, flagging which are reachable. Use to verify a dashboard install is wired up correctly.
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Track parcels and check delivery status for Australian and international couriers. Searches Gmail for dispatch/shipping emails and provides tracking links for all major Australian couriers including AusPost, StarTrack, Aramex, CouriersPlease, Sendle, Toll, Team Global Express, DHL, FedEx, TNT, Hunter Express, Border Express, Direct Freight Express, and UPS. Triggers: 'where is my parcel', 'track my order', 'has my package arrived', 'tracking status', 'check tracking', 'where is my delivery'.
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Deploy the dispatcher PCF for a third-party `.ppmplugin` control to a Power Platform environment via `pac pcf push`. The dispatcher PCF is the Studio-side control that dispatches the composite key `<name>/<receiver>` over the wrap shell's `SendMessagePlugin` bridge to the control's native module. Verifies deploy prereqs (Node.js 20+ with npm, .NET SDK, and active `pac auth`), then three confirmation gates — publisher prefix (2–8 chars; defaults to `pamext` or the last-used value from `.extension-state.md`), version bump (patch / minor / major / no-bump), target environment URL (from `pac org who`). Builds the PCF if needed, then pushes. Decoupled from /generate-pcf-companion so the engineer can scaffold and customize locally, then deploy when ready. Updates `.extension-state.md` with deployment history (timestamp, env URL, version, prefix used).
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。