「agreement」の検索結果

Drafts a mathematically balanced ALTA Settlement Statement for U.S. real estate closings, allocating debits and credits between buyer and seller with prorations, payoffs, lender fees, title charges, and transfer taxes. Enforces balance verification (seller credits minus debits equals cash to seller; buyer debits minus credits equals cash from buyer) and cross-references title commitment, loan documents, and purchase agreement. Use when preparing closing financials, settlement statements, HUD-equivalent documents, or real estate closing allocations.

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。

Drafts a standalone API Acceptable Use Policy (AUP) for incorporation by reference into a master API license or terms-of-service agreement. Produces a publication-ready template with prohibited-use matrix, developer security checklist, graduated enforcement framework, AI/ML training restrictions, and versioning playbook. Trigger when a user needs to draft or update an API AUP, separate behavioral rules from core API terms, define prohibited API uses, add enforcement or change-management mechanics, or mentions acceptable use policy, developer security requirements, or API enforcement.

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 structured summaries of mediation and arbitration proceedings, extracting outcomes, settlement terms, monetary amounts, obligations, releases, and enforcement steps. Trigger when the user needs to document mediation settlements, arbitration awards, or partial ADR resolutions from transcripts, agreements, mediator reports, or awards.

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。

Drafts jurisdiction-specific Advance Health Care Directive packages with agent appointment, living will instructions, HIPAA authorization bridge, organ donation preferences, and execution compliance checklists. Trigger when the user mentions advance directive, healthcare proxy, living will, health care agent, HIPAA authorization, medical power of attorney, end-of-life planning, capacity trigger planning, state-specific directive forms, witness/notary requirements for healthcare documents, or cross-state directive portability.

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。

Multi-LLM adversarial consensus loop — 3+ LLMs compete to find flaws in designs/specs until unanimous agreement is reached

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。

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。

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。

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。

Eliminate sycophantic agreement patterns in AI responses. Load via /skill anti-sycophancy.

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 receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

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 receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

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。

Combine independent work from two or more selected agents into one decision-ready research report, design, or proposal. Preserve useful complementary findings, develop stronger combined options, and present material alternatives only when they exist. Use when multiple perspectives should improve the product without forcing consensus or staging 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 when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

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。

Eliminate sycophantic agreement patterns in AI responses. Load via /skill anti-sycophancy.

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。

Abstracts one contract into a key-terms table with clause references, compares each term against the user's playbook of standard positions, and returns a DRAFT contract review pack: deviations and issues, open questions and a reviewer checklist. Flags governing law and never gives legal advice or enforceability or acceptability calls. Use when the user asks to "review this contract", "abstract the key terms", "summarise this MSA", "pressure-test this SOW against our playbook" or to compare an agreement with their standard positions. Do not use for a first pass on a stand-alone NDA, use nda-triage instead, or for one clause lined up across several documents, use clause-comparison-table instead. Drafts for human review; never approves, authorises or signs off.

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。

Compares one clause (liability, termination, confidentiality or any other) across several contracts, templates or successive versions and returns a DRAFT comparison table: verbatim clause text per document, the clause split into elements with every difference from the baseline highlighted and categorised, and neutral questions for counsel. Never says which wording is better or enforceable. Use when the user asks to "compare the liability caps across these five supplier contracts", "line up the termination clause in these three drafts", "show how the confidentiality clause changed between versions", "contrast this clause with our template" or "benchmark the indemnity wording across our customer agreements". Do not use for a whole-contract review, use contract-review-pack instead; for screening one NDA against standard positions, use nda-triage. Drafts for human review; never approves, authorises or signs off.

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。

Synthesises training survey responses and manager notes into a DRAFT training needs report by role: coded needs with record counts per role (n of N), the evidence type behind each count, anonymised quotes cited to record codes, disagreements between what staff report and what managers observe, gaps where a role is under-represented or a required skill has no evidence, and follow-up questions to settle before any course is designed. Never rates an individual, ranks a team or turns a count into a competence verdict. Use when the user asks to "analyse this training survey", "what training do our teams need", "summarise the manager feedback on skills gaps", "build a training needs analysis by role" or "which roles have the biggest skill gaps". Do not use for turning an agreed need into a course, use course-outline-builder instead; for exit interviews, use exit-interview-synthesis. Drafts for human review; never approves, authorises or signs off.

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。

Checks an extracted PFD register as a process model and returns findings and unknowns only: connectivity closure, stream numbering, presence of design conditions, equipment duty text, phase and service labels, package and off-sheet scope, boundaries, operating cases, and agreement between the drawing and attached process documents, then holds at gate G2. Creates no design values. Use when the user asks to "check the process model", "verify connectivity" or "is the PFD ready for enrichment" after gate G1 and before enrichment. Do not use for extraction from the drawing, use pfd-intake-and-extraction instead; do not use to propose lines or instruments, use piping-enrichment. Drafts for human review; never approves, authorises or signs off.

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。

Write the follow-up after a call in the owner's own voice instead of a bot template: recall the transcript, person card and full correspondence, extract agreements with an owner and due date, draft short and personal, show before/after against the old template, then send through the approval gate and file the result to the person card. Triggers: "/fa", "follow-up", "what should I write to <name> after the call", or a fresh call transcript landing in the vault.

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。

Eliminate sycophantic agreement patterns in AI responses. Load via /skill anti-sycophancy.

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 before responding to pressure for agreement, manufactured urgency, authority appeals, or requests to certify unsupported claims; separate evidence from persuasion and state uncertainty.

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 the user asks to "write influencer outreach", "follow up with a creator", "pitch a journalist, hunter, or launch partner", or "negotiate partnership terms"; produces personalized pitches, multi-touch follow-up sequences, negotiation scripts with objection handling, and a status pipeline tracker — the shared outreach mechanics engine for creator, media/analyst, launch-partner, and social-selling / advocate-recruitment targets. Not for finalizing signed agreements — use contract-helper; not for media-list tiering, embargo terms, or press-release structure — use press-media-relations. 达人邀约建联/合作谈判话术

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。