「ara」の検索結果

Use when you need to design, review, or improve validation in Quarkus applications — including Bean Validation on JAX-RS resources, @Valid on parameters and CDI beans, constraint groups, @ConfigMapping validation, custom constraints, nested DTO validation, and ExceptionMapper-based error mapping. This should trigger for requests such as Add validation support in Quarkus; Review Quarkus validation rules; Improve request validation in Quarkus REST APIs; Add custom validation constraints in Quarkus; Validate Quarkus @ConfigMapping properties. Part of cursor-rules-java project

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Use when you need to apply Java secure coding best practices — including validating untrusted inputs, defending against injection attacks with parameterized queries, minimizing attack surface via least privilege, applying strong cryptographic algorithms, handling exceptions securely without exposing sensitive data, managing secrets at runtime, avoiding unsafe deserialization, and encoding output to prevent XSS. This should trigger for requests such as Review Java code for secure coding. Part of cursor-rules-java project

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Scaffolds a complete .NET solution following Clean Architecture principles with proper layer separation (API, Application, Domain, Infrastructure). Creates project structure, dependency injection setup, and cross-cutting concerns configuration.

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Git worktree を使った並列開発時に使用。配置・ポート割当・環境コピー・クリーンアップを標準化する。

Plan the first months at a new Japanese employer after an offer is accepted, listing every expectation and promise made in interviews, the offer, or negotiation with its source, separating what is in writing from what was only said and what has no agreed measure, working out when the probation period ends and whether its criteria and conditions are known, and scheduling who to confirm what with before and after the start date. Use when a user has accepted an offer and wants to prepare for joining, make sure verbal promises such as remote days or a future role are confirmed, or understand what the probation period means for them; do not use to predict whether they will fit in or pass probation, to judge their manager or colleagues, to rule on the legality of probation terms, or to contact the new employer.

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。

Research a specific company before applying or interviewing by gathering facts from primary and official sources, recording the source and date behind every claim, and keeping anonymous or unverifiable material clearly separated from confirmed fact. Use when a user asks what a company actually does, how it makes money, what its published conditions are, whether a posting matches the company's own disclosures, or what to verify before an interview; do not use to predict hiring outcomes, to repeat review-site content as fact, or to bulk-crawl sites that prohibit automated access.

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。

Read a Japanese job posting closely and report what it actually states: base pay separated from fixed overtime allowance, the range converted to an hourly basis, required versus preferred requirements, and the terms left ambiguous. Use when a user wants a 求人票 or job description examined before applying, wants two postings compared on the same basis, or wants questions prepared about pay and working conditions; do not use to judge whether the user will be hired, to infer duties the posting does not state, or to evaluate the employer's reputation.

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。

Check the working conditions of a Japanese job offer item by item against the conditions an employer states in writing, compare the offer letter or 労働条件通知書 with the job posting and what was said in interviews, and separate what is confirmed in writing from what is still only verbal. Use when a user has received an offer, a working-conditions notice, or an employment contract and wants to know what is missing, what conflicts with earlier statements, and what to confirm before the acceptance deadline; do not use to rule on whether the terms are lawful, to decide whether to accept or decline, or to contact the employer on the user's behalf.

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。

Debrief a finished Otameshi Tenshoku trial from the employer's side: set the observed facts against the completion criteria agreed before the start, keep expectations added afterwards, second-hand or off-the-job observations and the company's own late or missing support apart, settle the hours actually worked separately from any evaluation, and draft feedback to the candidate that states facts, support gaps and what happens next without promising a hire or continuation the company has not decided. Use when a hiring manager, recruiter or small-business owner wants to review a trial, decide what to tell the candidate, or work out the settlement after a shortfall; do not use to judge the candidate's aptitude or predict a hire, to cut pay or demand unpaid rework because of dissatisfaction, to compare candidates, or to send the feedback, pay, or update records on the user's behalf.

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。

Help a user talk through whether to change jobs, stay, or change something in their current work, starting from uncertainty, distress, a vague sense of stagnation, an offer in hand, a counter-offer from the current employer, or pressure from family or colleagues. Clarify what matters, separate deadlines that order the next steps from the decision itself, compare conditional options, and agree on a small next step and a time to revisit it. Use when someone asks whether they should quit, wonders whether leaving is just running away, has second thoughts after receiving an offer or being asked to stay, feels stuck because others say it would be a waste, wants to leave soon after joining, or wants advice before deciding to start a job search; do not make the final stay-or-leave decision, evaluate offer terms, plan the resignation, or predict hiring outcomes.

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。

Review and revise Japanese job-application documents (entry sheets, rirekisho, shokumu-keirekisho) by checking each answer against the question asked, the stated character limit, and the evidence the applicant can actually support, then propose concrete rewrites the applicant decides on. Use when a user wants an ES or resume answer critiqued, tightened, or drafted from their own experience; to assemble a whole shokumu-keirekisho from an experience inventory, use resume-draft instead; do not use to invent experience, to judge pass or fail probability, or to submit an application.

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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.

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。

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.

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。

Draft or review an employer's Otameshi Tenshoku listing so a candidate can decide whether to apply: check item by item that the work, deliverable, out-of-scope tasks, required experience, support, hours, schedule, location, compensation, contract form and payment timing are stated, find open-ended, unpaid-company-work, guarantee, personal-attribute and unverifiable wording, and confirm that the hours, weekly availability, period, rate and budget hold together. Use when a hiring manager, recruiter or small-business owner wants a listing written from a plan, wants an existing draft or published listing reviewed before or after posting, or wants to know why applications are not coming; do not use to design the work itself (trial-work-design), to reply to applicants (applicant-reply), to state market rates, legal, tax or service conditions from memory, or to post or update the listing on the user's behalf.

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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.

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。

Designs pegRNAs and nicking guides for prime editing (PE) -- choosing the nick/strand, tuning the primer-binding site (PBS) and reverse-transcription template (RTT) as a per-locus panel, selecting the PE system (PE2/PE3/PE3b/PE4/PE5/PEmax/PE7), adding MMR-evading and PAM-disrupting silent edits, appending epegRNA 3' motifs (tevopreQ1/mpknot), and ranking with PRIDICT/DeepPrime. Covers twinPE/PASTE for large insertions and the prime-vs-base-editing decision. Use when designing a scarless point mutation, small insertion/deletion, or any of the 12 base conversions without a double-strand break, when efficiency is low and MMR inhibition or pegRNA stabilization is needed, or when routing a large insertion to an integrase method. Generic guide scoring and base editing are separate skills.

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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.

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。

Designs donor/repair templates for precise CRISPR knock-ins -- choosing the format (ssODN, long-ssDNA/Easi-CRISPR, dsDNA/plasmid, AAV6), sizing homology arms, placing the cut within ~10 bp of the edit, and adding a mandatory codon-checked blocking (PAM/seed) mutation so the edited allele is not re-cut. Frames the HDR-vs-NHEJ-vs-MMEJ pathway competition, the MMEJ (PITCh) and homology-independent (HITI/HMEJ) alternatives for post-mitotic cells, ssODN strand/asymmetry choice, phosphorothioate end-protection, and ranked HDR enhancers. Use when designing a donor for a point mutation, epitope/fluorophore tag, allele replacement, or knock-in, or when HDR efficiency is low. Guide design and base/prime editing are separate skills.

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Identifies non-coding RNAs (tRNA, rRNA, snoRNA, snRNA, riboswitches, sRNAs) using Infernal covariance-model search against Rfam, tRNAscan-SE 2.0 for tRNA, barrnap for rRNA, and ARAGORN for tmRNA, plus the small-RNA-seq boundary for miRNA and the transcript-assembly boundary for lncRNA. Covers the structure-conserved-not-sequence-conserved principle (why BLAST fails), GA-threshold and clan-competition correctness, tRNAscan-SE domain modes and pseudogene flags, rDNA copy-number collapse, and why homology annotation is a recall floor. Use when performing genome-wide ncRNA annotation, choosing the right tool for an RNA class, or interpreting ncRNA counts.

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Orders and orients assembled contigs into chromosome-scale scaffolds from long-range linking data, inserting N-gap spacers (adds no sequence). Covers Hi-C/Omni-C scaffolding (YaHS, SALSA2, 3D-DNA/Juicer), Hi-C read-mapping prerequisites (map each end separately, no mate rescue, dedup, enzyme-aware), reading the contact map for misjoins/inversions/false-duplications, manual curation in Juicebox/PretextView (the VGP/DToL standard), reference-guided scaffolding (RagTag) and its karyotype-erasure hazard, genetic-map (ALLMAPS) and Bionano optical-map integration, chimera-breaking before scaffolding, gap-filling, and telomere/contig-vs-scaffold-N50 QC (tidk). Use when turning contigs into chromosomes with Hi-C, integrating a linkage map or optical map, choosing a scaffolder by available linking data, or judging whether a chromosome-scale assembly is trustworthy.

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Generates, normalizes, and converts bedGraph signal tracks (4-column chrom/start/end/value, 0-based half-open) with bedtools genomecov, deepTools bamCoverage/bamCompare/bigwigCompare, bedtools unionbedg, and UCSC bedGraphToBigWig. Covers why a raw coverage bedGraph is not comparable across samples until normalized, the CPM/RPKM/BPM/RPGC normalization menu and the conserved-total assumption that makes them wrong under a global perturbation, the strict sorted-non-overlapping-chrom.sizes bedGraphToBigWig contract that silently corrupts a bigWig, effective-genome-size selection, and bin-size aliasing. Use when building or normalizing a coverage/signal track from a BAM, comparing tracks across samples or conditions, converting bedGraph to a browser-ready bigWig, or diagnosing a track that looks plausible but reports wrong heights.

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Assigns GO terms, Pfam/InterPro domains, KEGG orthologs, EC numbers, and product names to predicted proteins using eggNOG-mapper (orthology), InterProScan (domain signatures), and KofamScan (KEGG), routing specialized functions to dbCAN/antiSMASH/AMRFinderPlus/SignalP. Covers the orthology-vs-domain-vs-homology paradigms, the annotation-error percolation cascade, domain-presence-is-not-function, GO IEA circularity in enrichment, evidence tiering, and bit-score/coverage thresholds. Use when adding functional annotation to predicted genes, choosing between eggNOG-mapper and InterProScan, or judging how much to trust a functional label.

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Designs cytosine (CBE, C-to-T) and adenine (ABE, A-to-G) base-editor guides by positioning the target base at the activity-peak of the editing window (protospacer positions ~5-7, PAM-distal numbering), minimizing bystander edits for product purity, reading dinucleotide context (APOBEC1 TC favored / GC disfavored), and selecting the editor variant (BE4max, ABEmax, ABE8e, YE1/SECURE, TadCBE, CGBE, SpG/SpRY-BE). Covers knockout by premature stop (CRISPR-STOP/iSTOP) and splice-site disruption, the three off-target classes (Cas-dependent, Cas-independent DNA, RNA), outcome prediction (BE-Hive/DeepBE), and the base-vs-prime-vs-HDR decision. Use when installing a transition mutation without a double-strand break, knocking out a gene without indels, or choosing CBE vs ABE. Generic guide scoring, prime editing, and HDR donors are separate skills.

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Assign cell types from marker expression in IMC/MIBI data using clustering (PhenoGraph/FlowSOM/Leiden/Pixie), marker-based probabilistic classifiers (Astir), or image-context CNNs (CellSighter), covering the double-positive segmentation artifact, lineage-vs-state markers, the two spillover types, and why a "cell type" in imaging is conditioned on a segmentation guess. Use when phenotyping segmented IMC cells, choosing clustering vs classification, diagnosing implausible double-positive populations, separating lineage from functional markers, or transferring labels across a cohort.

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。