'fid' 검색 결과

Check whether a user may start side work alongside their current job, by reading the employer's own rules and contract clause by clause: whether side work is prohibited, needs prior permission, or only a notification, and which duties the planned side work could touch (non-compete, confidentiality, exclusive attention to the main job, use of company assets and information, combined working hours). Separate what is confirmed in a document from what is hearsay, and produce the questions to ask the employer plus the facts an application or notification will need. Use when someone with a main job is considering side work, freelance or gyomu-itaku work, a second part-time job, or paid trial work for another company, and needs to know what their own employer's rules require first; do not use to rule on whether a clause is lawful or enforceable, to help conceal side work from an employer or avoid filing obligations, to predict whether permission will be granted, or to submit the application or contact the employer.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Assemble a Japanese shokumu-keirekisho (career history document) from an experience inventory, choosing between reverse-chronological, chronological, and skills-based layouts, mapping the target posting's requirements to the experiences that can support them, and drafting the summary, work history, skills, and self-PR so that each sentence stays within what its evidence supports and confidential details are abstracted. Use when a user wants to write or rebuild a whole shokumu-keirekisho for a specific posting or as a general version, or wants to decide which experiences to include and in what order; do not use to invent experience, numbers, titles, or qualifications, to predict whether it will pass screening, to fill in a rirekisho form, or to submit it anywhere.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Check the terms of a specific side-work assignment offered as gyomu-itaku or freelance work in Japan, item by item: what the client has actually put in writing about the deliverable, the fee, the payment due date, what counts as out of scope, how many revisions are included, who bears expenses, who owns the result, confidentiality, and how either side can end it. Convert the fee into an effective hourly figure over the hours the work will really take including meetings, revisions and unpaid preparation, and count the days from delivery to the payment due date. Use when someone is offered or is discussing a paid side job, a freelance assignment, spot consulting, or paid trial work and wants to know what is still unwritten before starting; do not use to judge whether the fee is fair or the terms lawful, to decide whether to accept, to draft or sign the contract for the user, or to check whether their employer's rules permit side work, which is sidework-rules-check.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Nominates and assesses CRISPR off-target sites genome-wide. Enumerates candidate sites by mismatch and bulge tolerance with Cas-OFFinder/CRISPRitz, ranks them with the published CFD score (SpCas9-only, relative ranker) or MIT/CRISTA/energy models, runs variant-aware screening against gnomAD/individual genomes (CRISPRme), and frames the empirical genome-wide discovery assays (GUIDE-seq, CIRCLE-seq, CHANGE-seq, DISCOVER-seq, Digenome-seq) and high-fidelity nuclease choice (HiFi Cas9, Sniper-Cas9, eSpCas9, SpCas9-HF1). Use when assessing guide RNA specificity, choosing among candidate guides, screening a therapeutic guide against population variation, or planning empirical off-target validation. Distinguishes predicted vs detected vs validated. On-target activity scoring and deaminase (Cas-independent) base/prime-editor off-targets are separate skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors are separate skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Pull pre-computed ortholog calls from public databases (OrthoDB, Ensembl Compara, OMA browser, eggNOG, PANTHER, KEGG Orthology, HomoloGene) via their REST APIs. Use when orthologs are already curated upstream, when the question is "what is the X ortholog of Y" rather than "how to infer orthology de novo", when batch-mapping gene IDs across species, or when comparing the resources for consensus calls. Encodes confidence-level semantics, 1:1 vs 1:many vs many:many, HomoloGene deprecation, and when to defect to de novo computation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Query protein-protein and gene interaction databases (STRING, BioGRID, IntAct, SIGNOR, Reactome, HuRI, HuMAP, OmniPath, ConsensusPathDB, DIP). Use when building PPI networks, choosing between physical vs functional vs genetic interactions, signed/directed vs undirected, high-throughput vs curated, picking confidence thresholds, aggregating across resources, or navigating license constraints. Encodes the database decision matrix, STRING v12 channel semantics, OmniPath as meta-database, SIGNOR for signed signaling, and per-resource rate limits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / BAGEL2 / Chronos based on quality grade, picking a normalization strategy from QC signatures, or evaluating whether an in-vivo screen retained adequate library complexity.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Tests associations between categorical variables in clinical data using chi-square, Fisher's exact, Boschloo, Cochran-Mantel-Haenszel, and modern McNemar variants with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen). Use when analyzing categorical outcomes, paired binary endpoints, or testing treatment-outcome independence in confirmatory or exploratory clinical trials.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Computes and interprets treatment effect measures (OR, RR, RD, HR, NNT) with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen, MOVER, profile likelihood, Bender NNT) and reports marginal vs conditional estimands per FDA 2023 covariate adjustment guidance. Use when reporting treatment effects in confirmatory trials, comparing effect sizes across studies, or constructing forest plots.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reflection-first problem solving methodology for Convex development. Use before implementing any solution to ensure proper root cause analysis, 98% code confidence, and minimal change scope.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

A modern, graphic, editorial-poster aesthetic — warm and confident — built on alternating cream and burnt orange sections, an amber brand color.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Hand-drawn paper-wireframe template — white paper background, monochromatic ink palette, SVG turbulence "wobble" filters for pen-quiver authenticity, handwritten fonts (Caveat / Kalam / Ma Shan Zheng / Long Cang), wavy dividers, sketch-rect overlays, marginalia annotations. For PRD illustrations, IA flow docs, low-fidelity layout exploration, "draft / not final" stakeholder communication. Three skeletons (single-page editorial / app multi-screen flow / IA sitemap) — pick one up front based on the artifact, do NOT inherit only the brush strokes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze a completed phase diff for high-confidence behavior-preserving simplifications and apply only explicitly approved proposals. Use after execution and before review to reduce duplication, dead code, needless complexity, or avoidable inefficiency.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement test-driven development (TDD) workflow using the red-green-refactor cycle. Use when writing new features, fixing bugs, or refactoring existing code. Always write the failing test first, then implement minimal code to pass, then refactor. Essential for ensuring code reliability, preventing regressions, improving design through testability requirements, documenting expected behavior through tests, enabling confident refactoring, and maintaining high code quality standards throughout the development process.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Write comprehensive end-to-end tests that verify complete user workflows, integration between components, and system behavior from user perspective using Playwright, Cypress, or similar frameworks. Use when testing user flows, verifying feature integration, testing across real browsers, ensuring UI interactions work correctly, validating form submissions end-to-end, testing authentication flows, catching regressions, automating QA processes, testing API integrations, or building confidence in production deployments.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Chief Security Officer mode. Infrastructure-first security audit: secrets archaeology, dependency supply chain, CI/CD pipeline security, LLM/AI security, skill supply chain scanning, plus OWASP Top 10, STRIDE threat modeling, and active verification. Two modes: daily (zero-noise, 8/10 confidence gate) and comprehensive (monthly deep scan, 2/10 bar). Trend tracking across audit runs. Use when: "security audit", "threat model", "pentest review", "OWASP", "CSO review". (gstack) Voice triggers (speech-to-text aliases): "see-so", "see so", "security review", "security check", "vulnerability scan", "run security".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

HTML -> UCUF (Cocos Creator UI) conversion skill. Use for turning a complete HTML source package with ui-design-tokens.json and colors_and_type.css into Cocos usable layout/skin/screen JSON, then validating with rule guard, visual fidelity risk, runtime interaction smoke, Cocos Editor final gate, and regression evidence.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors are separate skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Nominates and assesses CRISPR off-target sites genome-wide. Enumerates candidate sites by mismatch and bulge tolerance with Cas-OFFinder/CRISPRitz, ranks them with the published CFD score (SpCas9-only, relative ranker) or MIT/CRISTA/energy models, runs variant-aware screening against gnomAD/individual genomes (CRISPRme), and frames the empirical genome-wide discovery assays (GUIDE-seq, CIRCLE-seq, CHANGE-seq, DISCOVER-seq, Digenome-seq) and high-fidelity nuclease choice (HiFi Cas9, Sniper-Cas9, eSpCas9, SpCas9-HF1). Use when assessing guide RNA specificity, choosing among candidate guides, screening a therapeutic guide against population variation, or planning empirical off-target validation. Distinguishes predicted vs detected vs validated. On-target activity scoring and deaminase (Cas-independent) base/prime-editor off-targets are separate skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Query protein-protein and gene interaction databases (STRING, BioGRID, IntAct, SIGNOR, Reactome, HuRI, HuMAP, OmniPath, ConsensusPathDB, DIP). Use when building PPI networks, choosing between physical vs functional vs genetic interactions, signed/directed vs undirected, high-throughput vs curated, picking confidence thresholds, aggregating across resources, or navigating license constraints. Encodes the database decision matrix, STRING v12 channel semantics, OmniPath as meta-database, SIGNOR for signed signaling, and per-resource rate limits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Pull pre-computed ortholog calls from public databases (OrthoDB, Ensembl Compara, OMA browser, eggNOG, PANTHER, KEGG Orthology, HomoloGene) via their REST APIs. Use when orthologs are already curated upstream, when the question is "what is the X ortholog of Y" rather than "how to infer orthology de novo", when batch-mapping gene IDs across species, or when comparing the resources for consensus calls. Encodes confidence-level semantics, 1:1 vs 1:many vs many:many, HomoloGene deprecation, and when to defect to de novo computation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / BAGEL2 / Chronos based on quality grade, picking a normalization strategy from QC signatures, or evaluating whether an in-vivo screen retained adequate library complexity.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.