「collect」の検索結果

Autonomous Reforge-guided refactor workflow for the Humans repository. Use when the user wants Codex to target a section such as Shifts, Users, Teams, Tickets, Camps, or Store, create a dedicated worktree/branch from origin/main, run iterative architecture-focused improvements, score each stage with Reforge, gate commits through a score-blind read-only architecture review, append score and verdict details to commit messages after review acceptance, push progress, and open a PR when the loop reaches stasis.

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Autonomous tech-debt reduction workflow for the Humans repository. Use when the user wants Codex to improve high-value code quality issues in a dedicated git worktree branched from origin/main, commit each improvement separately, push progress, and continue until diminishing returns.

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。

Refresh drift-prone documentation against current code. Reads docs/architecture/freshness-catalog.yml, diffs against the last sweep's upstream/main anchor, regenerates mechanical entries, processes editorial markers, and opens one PR per sweep with a report file.

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When the user wants to create or optimize popups, modals, overlays, slide-ins, or banners for conversion purposes. Also use when the user mentions "exit intent," "popup conversions," "modal optimization," "lead capture popup," "email popup," "announcement banner," "overlay," "collect emails with a popup," "exit popup," "scroll trigger," "sticky bar," or "notification bar." Use this for any overlay or interrupt-style conversion element. For forms outside of popups, see form-cro. For general page conversion optimization, see page-cro.

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Design shotgun: generate multiple AI design variants, open a comparison board, collect structured feedback, and iterate. Standalone design exploration you can run anytime. Use when: "explore designs", "show me options", "design variants", "visual brainstorm", or "I don't like how this looks". Proactively suggest when the user describes a UI feature but hasn't seen what it could look like. (gstack)

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Triage AEM Workflow issues on AEM as a Cloud Service by classifying symptoms, gathering the right logs and metrics, and mapping to runbooks or Splunk searches. Use when the user asks for workflow activity/errors on a Cloud Service host, needs to classify a Jira ticket, or wants to know what to collect for workflow debugging.

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Survey available blocks from local AEM Edge Delivery Services project and Block Collection to understand the block palette available for authoring. Returns block inventory with purposes to inform content modeling decisions.

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Use only when the user explicitly types `/orchestrate goal` to decompose a large task, spawn a tree of parallel cloud-agent workers/subplanners/verifiers via the Cursor SDK, and collect structured handoffs; do not invoke autonomously.

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Use this skill when the user requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade analytical report. This skill operates in two phases — (1) generating a structured analysis framework with chapter skeleton, data query requirements, and analysis logic, and (2) after data collection by other skills, producing the final consulting-grade report with structured narratives, embedded charts, and strategic insights.

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Annotates bacterial and archaeal genomes (isolates, MAGs, plasmids) with Bakta (active versioned databases, NCBI-compliant output) or Prokka (legacy), producing GFF3/GenBank/EMBL/FASTA with INSDC locus tags. Covers Bakta-vs-Prokka-vs-PGAP-vs-DFAST choice, light-vs-full database tiers, translation-table selection (11/4/25), archaeal and leaderless-gene caveats, the small-ORF blind spot, pseudogene-vs-phase-variation, the pangenome re-annotation trap, and submission compliance. Use when annotating a newly assembled prokaryotic genome, choosing an annotation tool, re-annotating a collection for pangenomics, or preparing annotations for NCBI/DDBJ submission.

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Call copy number variants with the GATK best-practices workflows — the somatic CNV pipeline (CollectReadCounts, DenoiseReadCounts with tangent normalization, ModelSegments, CallCopyRatioSegments) and the germline GATK-gCNV pipeline (DetermineGermlineContigPloidy, GermlineCNVCaller cohort/case mode, PostprocessGermlineCNVCalls). Covers panel-of-normals construction, AnnotateIntervals/FilterIntervals, allelic-count integration, and QS-based filtering. Use when integrating CNV calling into a GATK variant pipeline, calling rare germline CNVs from an exome cohort, deciding between the somatic and germline GATK workflows, or diagnosing why tangent normalization removed a real event or why gCNV output has low precision.

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Standardizes molecular structures using ChEMBL chembl_structure_pipeline and RDKit rdMolStandardize covering sanitization, salt/solvent stripping, neutralization, tautomer canonicalization, stereochemistry standardization, mixture handling, and isotope normalization. Explicitly compares ChEMBL pipeline, canSARchem, and PubChem standardization choices. Use when preparing libraries for QSAR training, joining datasets across sources, deduplicating compound collections, or building canonical compound registries.

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Discovers de novo motifs and tests known motif enrichment in ChIP-seq, ATAC-seq, or other peak sequences using HOMER, MEME-ChIP (STREME, CentriMo, TOMTOM, FIMO), monaLisa, and AME. Handles background selection (GC-matched, dinucleotide-shuffled, Markov order-2, peak-flanks), motif databases (JASPAR 2024 CORE PWMs, JASPAR 2026 deep-learning collection, HOCOMOCO v12, HOMER built-in), centrally-enriched motif testing, and differential motif analysis. Use when identifying TF binding motifs in peaks, testing for known TF enrichment, scanning for motif instances, comparing motif content between conditions, or interpreting motifs from deep learning models.

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Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2025 Nat Genet; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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。

Use this skill when a driver is returning to safety-sensitive duty after a positive test or refusal. Covers the SAP clearance, RTD test requirements (observed collection), and Clearinghouse update sequence.

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。

Recipe for creating or changing a floating window panel. Use when adding a window, editing a window component, adding persistence, onCollectData, or ephemeral mode, wiring the Tools grid, or a window fails to restore after reload. NOT for WindowPanel drag/resize/tray internals (use window-panels).

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next/dynamic code splitting and build-graph cost; first stop for build failures. Use before lazy-loading or deferring a heavy component, adding a dynamic import, React.lazy, or ssr: false; on 'window is not defined' or a hydration mismatch; shrinking the bundle; or on 'build failed', OOM, SIGKILL, a slower build, or 'Collecting page data'.

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Collect and submit developer feedback to the LiveAvatar team. Use when: (1) A LiveAvatar integration is done, working, finished, or complete, (2) The user says "it works", "we're done", "that's it", "ship it", (3) The user is frustrated, stuck, or giving up — "this is broken", "this doesn't work", "I'm stuck", "I give up", "this is frustrating", "I want to report an issue", (4) The user explicitly asks to give feedback, report a bug, file an issue, or share a suggestion about LiveAvatar, (5) You've seen 3+ failed attempts at the same integration step, (6) You just finished writing or generating LiveAvatar integration code for the user.

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。

Use this skill when the user requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade analytical report. This skill operates in two phases — (1) generating a structured analysis framework with chapter skeleton, data query requirements, and analysis logic, and (2) after data collection by other skills, producing the final consulting-grade report with structured narratives, embedded charts, and strategic insights.

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。

Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories. Covers deleted commit recovery, force-push detection, IOC extraction, multi-source evidence collection, hypothesis formation/validation, and structured forensic reporting. Inspired by RAPTOR's 1800+ line OSS Forensics system.

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。

Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory

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Deploy your own Open-Inspect instance. Use when the user wants to set up, deploy, or onboard to Open-Inspect. Guides through repository setup, credential collection, Terraform deployment, and verification with user handoffs.

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Fetch personalized daily horoscope forecasts from zodiac-today.com API based on natal chart calculations. Use when a user wants: (1) daily guidance on what activities to pursue or avoid, (2) life planning help — best days for interviews, travel, romance, important decisions, (3) energy/focus/luck/romance forecasts to optimize their schedule, (4) lucky colors and numbers for the day, (5) future date analysis for planning events, trips, or milestones (paid tiers). Triggers: horoscope, zodiac, star sign forecast, daily guidance, lucky day, best day to, astrology advice, what should I do today, is today a good day for, plan my week astrology. Required env: ZODIAC_API_KEY (hsk_ API key), ZODIAC_PROFILE_ID (birth chart profile ID). Collects sensitive PII (email, birth date, birth city) for natal chart — requires user consent.

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Pyramid multi-agent orchestration for OpenClaw: routes objectives from a CEO agent down through departments, services and employees via sessions_send / sessions_spawn, collects and merges results, enforces handoff contracts, and writes the final deliverable back to the originating session.

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。