'discovery' 검색 결과

Conduct a Marty-Cagan-style opportunity assessment interview and produce a ~2-page Opportunity Brief in Confluence. Covers business objective, customer, problem, success metric, current alternatives, assumptions/risks, and what we don't know yet. Triggers on "opportunity brief", "opportunity assessment", "discovery brief", "who is this for", "why are we building this", "validate this idea", "product discovery", or any request to frame a feature before implementation. One question at a time. Records accepted research gaps as structured Confluence Decision pages with bidirectional links.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Prepares a discovery call brief from what the user has on a prospect (CRM record, inbound form, emails, notes, public material the user supplies): what is known with sources, gaps against the qualification dimensions, hypotheses to test, questions in priority order and what to listen for. Returns a DRAFT Markdown brief in the chat. Use when the user asks to "prep me for the discovery call with <prospect>", "what should I ask on this first call", "intro call brief", "questions for the qualification call" or "what do we know before we speak to them". Do not use for scoring leads against a rubric, use lead-qualification-scorer instead; for an existing customer's account review use account-plan-builder. Drafts for human review; never approves, authorises or signs off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert en eDiscovery (document review, data processing, ESI, litigation hold, TAR)

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

open Issue を triage して「次の仕事候補（N 件 + 推奨 1 件）」を窓口が人間へ提示する。 候補はオペレーターが書いたゴール台帳（registry/goals/）の条項に当たるものだけで、条項順に並ぶ。 tools/work_discovery_scan.py を 1 回実行し、その候補 JSON を 設計書 §5.2 / §12 の人間可読フォーマットでレンダリングするところで停止する（propose-only）。 起動主体は窓口に限定。手動 / イベント起動のみ（常駐 /loop なし）。 「次の仕事候補出して」「triage して」「次なにやる？」や PR マージ後の proactive next-dispatch で窓口が手動起動する。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes alternative splicing from PacBio Iso-Seq (HiFi, Kinnex/MAS-Iso-seq) and Oxford Nanopore (direct cDNA, direct RNA, R10.4.1+) long-read RNA-seq with full-isoform resolution. Tools include FLAIR (correct/collapse/quantify/diffSplice for PacBio + ONT), IsoQuant (de-novo or annotation-guided isoform discovery 2024 SOTA), Bambu (annotation-aware Bayesian discovery + quantification with Novel Discovery Rate), SQANTI3/SQANTI-LR (isoform classification: FSM/ISM/NIC/NNC + artifact flags), rMATS-long (event calling on long-read isoforms), and minimap2 (-ax splice:hq for HiFi; -ax splice -k14 for ONT cDNA; add -uf only for direct RNA or stranded cDNA preps). Solves microexon detection, recursive splicing, complex multi-exon isoforms, and DTU without transcript-quantification uncertainty. Use when short-read AS limitations (anchor length, complex isoforms, microexons, recursive splicing, transcript ambiguity) demand full-isoform resolution.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run Mom Test–style customer-discovery interviews to validate or kill an unbuilt idea — generate a non-leading interview guide, conduct or coach the conversations, and synthesize signal vs compliments. Load when the user asks to do customer discovery, run problem interviews, validate an idea with users, run a Mom Test, design an interview guide, or says "talk to customers", "validate the problem", "interview users", "Mom Test this", "did real users want it", "synthesize my interviews", "I just talked to N people". Sub-skill of `venture-exploration`. Hard-bans "would you use this?", solution-pitching, friend/family-only ICP, and treating compliments as validation. Calls `secure-*` before synthesizing any pasted external transcripts.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes alternative splicing from PacBio Iso-Seq (HiFi, Kinnex/MAS-Iso-seq) and Oxford Nanopore (direct cDNA, direct RNA, R10.4.1+) long-read RNA-seq with full-isoform resolution. Tools include FLAIR (correct/collapse/quantify/diffSplice for PacBio + ONT), IsoQuant (de-novo or annotation-guided isoform discovery 2024 SOTA), Bambu (annotation-aware Bayesian discovery + quantification with Novel Discovery Rate), SQANTI3/SQANTI-LR (isoform classification: FSM/ISM/NIC/NNC + artifact flags), rMATS-long (event calling on long-read isoforms), and minimap2 (-ax splice:hq for HiFi; -ax splice -k14 for ONT cDNA; add -uf only for direct RNA or stranded cDNA preps). Solves microexon detection, recursive splicing, complex multi-exon isoforms, and DTU without transcript-quantification uncertainty. Use when short-read AS limitations (anchor length, complex isoforms, microexons, recursive splicing, transcript ambiguity) demand full-isoform resolution.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Automated discovery and matching of agent skills for dynamic task routing and capability assessment

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Filesystem auto-discovery of App Router pages into navigable index pages. Use when creating an index/listing page, adding route directories, converting hard-coded route configs to auto-discovery, or adding a route-listing display variant.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build web discovery into applications and agent workflows with Firecrawl search. Turn a query into candidate URLs, select useful sources, and decide whether to retrieve page content for further extraction or answers with cited sources.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding web sources for answers with citations
• Discovering companies, competitors, or topics
• Creating a shortlist of pages for deeper research

Build and organize Claude Code plugins with guidance on directory layout, configuration files, commands, agents, skills, and hooks. Learn how automatic component discovery works and how to reference bundled files across different installation locations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Scaffolding a Claude Code plugin
• Organizing commands, agents, and skills
• Configuring paths for different installation locations

Find the smallest set of tools suited to a task, check their required inputs and effects, and inspect the results. Use a small read-only check when the environment or target is uncertain.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing suitable tools from a large collection
• Checking required inputs before a tool call
• Investigating failures caused by incorrect parameters

Research current web information with Parallel CLI and organize findings with supporting sources. The skill covers search, page extraction, detailed reports, adding sourced fields to existing lists, finding matching entities, and recurring monitoring of web changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Research current information and locate academic sources
• Extract content from public webpages and PDFs
• Add sourced information to company or product lists

Analyze pooled CRISPR screens from FASTQ reads or guide-count tables using MAGeCK. Validate inputs, assess library and replicate quality, and rank enriched or depleted genes with effect sizes and false discovery rates, which estimate false-positive proportions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Counting guide reads from FASTQ files
• Checking library representation and replicate consistency
• Comparing treatment and control screens

Process molecular datasets in Python through a simpler interface to RDKit, a chemistry toolkit. Convert and standardize structures, calculate molecular properties, compare and cluster compounds, generate 3D conformations, and visualize results for drug discovery workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Load and standardize molecular datasets
• Calculate molecular properties and similarities
• Cluster compounds and select diverse subsets

Automate daily literature discovery across multiple academic sources. Score and select relevant papers, read abstracts or full texts, deliver structured digests through messaging platforms, and archive classified notes while removing duplicate records.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Receive a daily digest of relevant research papers
• Rank candidate papers against research priorities
• Archive literature notes without duplicate records

Build and maintain an inventory of hardware, software, and cloud resources. Use guidance on automated discovery, ownership records, tagging checks, and integration with a configuration database to support operations and audit preparation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Defining fields for an IT asset inventory
• Planning resource discovery across AWS, Azure, and GCP
• Checking ownership and cost allocation tags

Guide authorized API security assessments from endpoint discovery to documented findings. Use a staged workflow to examine authentication, access permissions, input handling, data exposure, and request limits across REST, GraphQL, WebSocket, and SOAP APIs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning an authorized API security assessment
• Reviewing JWT and OAuth 2.0 authentication
• Checking permissions across users and roles

Guide authorized security assessments of REST, SOAP, and GraphQL APIs. Organize endpoint discovery, authentication checks, access control tests, and input testing, then document discovered weaknesses and evidence of unauthorized data access.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan API checks for an authorized bug bounty assessment
• Check whether users can access another account's records
• Review GraphQL schema exposure and request limits

Assess authorized APIs through a ten-stage workflow covering endpoint discovery, authentication, access permissions, input handling, and request limits. Collect reproducible evidence and turn findings into regression checks that can run in a development pipeline.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review API authentication and access permissions
• Assess GraphQL and WebSocket security
• Check request limits and unintended data exposure

Browse registered trading strategies and compare evidence from backtests, which simulate trades on historical data. Filter by market conditions, trade counts, risk-adjusted returns, and cost feasibility, inspect evidence age, and rebuild the evidence cache from local runs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Browsing registered trading strategies
• Finding strategies with evidence for falling or rising markets
• Checking a strategy's evidence quality and age