358 件 ・ 関連度順
概要と使いどころ
Use this skill when the user asks what information a Stripe Connect connected account must provide for verification, onboarding, KYC, or account requirements; when they need to compare requirements between connected-account setups; or when they ask which verification fields, documents, or business details are required for a particular platform country, account country, business type, dashboard, service agreement, or capability.
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。
Generates a complete, customized Non-Disclosure Agreement with plain English annotations, tailored to the specific parties and situation
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 privacy policies, terms of service, disclaimers, and legal notices. Creates GDPR-compliant texts, cookie policies, and data processing agreements. Use PROACTIVELY for legal documentation, compliance texts, or regulatory requirements.
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。
Create employment contracts, offer letters, and HR policy documents following legal best practices. Use when drafting employment agreements, creating HR policies, or standardizing employment documentation.
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。
Compare two implementations of the same thing — a port (R↔Python↔Stata), a reimplementation, a replication package, a refactor, or a new version against the old — so that agreement means something. Freeze inputs first, inventory every expected output, test the comparator itself, compare every channel (not just the headline number), and give each divergence a stable ID and a smallest witness. Use for cross-language parity, replication, upgrade/regression gates, or whenever "the numbers match" is about to license a claim.
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。
Generate a structured response-to-referees document from a referee report and the revised manuscript. Maps each referee comment to the specific revision, classifies coverage (addressed / partially / deferred / disagreement), and drafts polite but firm responses. Use during the R&R (revise-and-resubmit) stage of paper revision.
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。
Before rejecting a proposal or reflexively agreeing, build the strongest faithful opposing case, state agreement conditions, then update or reaffirm.
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。
Decode a brand deal or UGC contract before signing — usage rights, exclusivity windows, whitelisting, payment terms, and kill clauses ranked 🔴🟡🟢 by what they can cost a creator, plus the counter-ask email. Use when a creator says 'is this brand deal fair', 'what does perpetual usage mean', 'they sent me a contract', or 'should I sign this collab agreement'. Produces a clause-by-clause decode, a money-math check on the rate, and a ready-to-send negotiation email. Not legal advice.
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。
Scan a contract you're about to sign in plain language — surface the clauses that could bite you, what they mean, and what to question or renegotiate. Use when asked to check this contract before I sign, what am I agreeing to, are there red flags in this agreement, or explain this contract's risky bits. Produces a plain-English flag list of the risky/unusual clauses (auto-renewal, lock-in, liability, IP, termination, fees), what each means for you, questions to ask, and suggested changes — flagging when it's important enough for a lawyer. Not legal advice.
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。
Plan a Chinese campus recruitment season (校招: 秋招 and 春招), including internships that convert to offers (实习转正): the timeline, a target company list, a one-page campus CV, online application answers, written tests and interview rounds, and choosing between offers and signing the tripartite agreement (三方协议). Use when asked 秋招怎么准备, 帮我做校招计划, 校招简历, 网申问题怎么写, 群面, 三方协议, 怎么选 offer, or plan my campus recruitment in China. Produces a season timeline to confirm with each company, a tiered company list, a campus CV, application answer drafts, a test and interview preparation plan, and an offer comparison.
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 when asked 怎么给老师发消息, 跟班主任沟通, 孩子在学校被欺负怎么跟老师说, 对老师的做法有意见, 请假怎么写, 家长群里怎么说话, or write a message from a parent to a teacher in China. Produces a ready-to-send WeChat or note message in Chinese, polite and specific, for the situation (asking, leave, a concern, a disagreement, bullying, thanks), a calmer version if the parent is upset, what to say if the teacher calls back, the escalation path if it is not resolved, and 家长群 etiquette.
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。
Run a family meeting to make a big care decision together. Use when asked help me run a family meeting about care, we need to decide together about mom's care, my siblings and I disagree about our parent, or facilitate a care decision. Produces an agenda and structure for the meeting, how to prepare (facts, options, everyone's input), ground rules to keep old family dynamics from derailing it, how to include the person being cared for, ways to work through disagreement toward a decision, and clear next steps with owners. Not legal, medical, or financial advice.
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。
Decode a care-home contract before a parent moves in — the fee-escalation clause with no cap, the needs-can-no-longer-be-met eviction trigger, the guarantor line that quietly makes you personally liable, and the after-death charges nobody mentions on the tour. Use when asked to review a care-home or nursing-home contract, what does this admission agreement mean, can they raise the fees, or can they make my parent leave. Produces a clause-by-clause decode ranked by financial and eviction risk, the questions to put in writing before signing, and the negotiate-or-verify list. Pairs with long-term-care-options for choosing the home; this is for the contract. Not legal advice.
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。
Compare independent opinions from several models or contexts without inflating agreement. Use when: wanting a second opinion or debate, or summarizing several reviewers' results.
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 when designing or auditing experiments for an ACL paper, covering tuned LLM baselines, multi-dataset and multilingual evaluation, statistical significance and variance, human evaluation with agreement reporting, contamination and prompt-sensitivity controls, ablations, and error-analysis expectations in NLP reviewing.
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 when a Simulink model is incompatible with Simulink Design Verifier (sldvcompat returns false, or an SLDV analysis errors out on an unsupported construct) and needs to be made analyzable. Diagnoses the incompatibility, applies the matching fix to a copy, and confirms the copy is compatible; optionally raises confidence the fix preserved behavior via a back-to-back consistency replay (agreement on the generated tests, not a proof of equivalence). Do NOT use for running test generation, design error detection, or requirement verification themselves — only for making a model compatible so those can proceed.
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。
Detects acquired antimicrobial-resistance determinants and chromosomal point-mutation resistance in bacterial assemblies using AMRFinderPlus, ResFinder 4.0 (acquired + PointFinder), CARD-RGI, abritAMR, staramr, and species-specific callers (TB-Profiler, Mykrobe). Harmonises cross-tool output via hAMRonization, contextualises determinants with mobile-genetic-element annotation (MOB-suite, PlasmidFinder, MobileElementFinder, ICEberg), predicts phenotype against EUCAST or CLSI breakpoints, and translates calls into WHO GLASS reporting categories. Use when screening clinical or surveillance isolates for AMR, distinguishing acquired vs intrinsic vs point-mutation resistance, calling rpoB / katG / pncA / gyrA / mgrB mutations, reconciling AMRFinderPlus vs RGI vs ResFinder disagreement, contextualising carbapenemases or mcr alleles on plasmids, predicting susceptibility from genotype against the WHO Mtb 2nd-edition catalogue, or building a hAMRonized multi-lab AMR surveillance pipeline.
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。
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.
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。
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
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。
Map N6-methyladenosine (m6A) RNA modifications at single-nucleotide resolution using miCLIP (Linder 2015), miCLIP2 + m6Aboost machine learning (Kortel 2021), GLORI (Liu 2023, antibody-free chemical conversion), DART-seq (Meyer 2019, APOBEC1-YTH fusion), m6Anet (nanopore direct RNA), or MeRIP-seq with calibration. Use when distinguishing antibody-based from antibody-free m6A detection methods, applying the DRACH motif constraint, reconciling cross-method disagreements (DART 44% in DRACH vs GLORI), or detecting m6Am at the cap.
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。
Identifies differentially bound ChIP-seq regions between conditions using DiffBind, csaw (sliding windows), DESeq2/edgeR/PyDESeq2 on count matrices, NormR (control-aware), or MAnorm2. Distinguishes three distinct normalization problems (composition bias, trended bias, global shifts) and matches each to its appropriate fix including spike-in scaling. Use when comparing ChIP-seq binding between experimental conditions, choosing normalization for global vs local changes, integrating spike-in data, or reconciling DiffBind/DESeq2 disagreement.
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 asks what information a Stripe Connect connected account must provide for verification, onboarding, KYC, or account requirements; when they need to compare requirements between connected-account setups; or when they ask which verification fields, documents, or business details are required for a particular platform country, account country, business type, dashboard, service agreement, or capability.
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。
Run all four review skills (investor, customer, operator, skeptic) on a business plan in sequence, then auto-decide where verdicts agree and surface only disagreements + taste decisions to the user. One command = full review gauntlet, intelligently filtered. Use when a plan is ready to be stress-tested before commit. Triggered by: 'panel review', 'review panel', 'run all reviews', 'review gauntlet', '审议会', '四方评审'.
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。
Produce a research report from the vault: scope the question against existing pages, name the gaps, and write findings with citations, disagreements and limits. Use this skill when the user asks for a research report, a deep write-up on a topic, or wants to understand a subject thoroughly using what they have collected. Do NOT use for a quick answer from the vault, for drafting an article in the user's voice, or for summarising a single source.
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。