871 件 ・ 関連度順
概要と使いどころ
客户需求发现与澄清助手：当用户是销售、客户成功或售前，拿到客户模糊、宽泛、缺少产品边界的需求，需要先在内部最多五轮补齐关键事实，再生成一次性客户澄清问题清单、需求摘要与通用技术可行性判断时使用；当确认需求将落入 StyleWork 时加载可选产品与 UI 上下文，并可在信息足够或明确要求时输出带假设标记的轻量 Demo。不要用于直接报价、承诺交期、替代正式 PRD 或在信息不足时假装已有能力。
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 California-compliant privilege logs for withheld or redacted discovery materials under CCP 2031.240. Use when the user mentions privilege log drafting, California privilege log, CCP 2031.240, attorney-client privilege logging, work product designation, Evid. Code 952/954, CCP 2018.030, redaction logging, meet-and-confer privilege disputes, waiver analysis, common interest doctrine, or asks for help documenting withheld documents. Also trigger on references to Hernandez v. Superior Court, Costco Wholesale, or Wellpoint.
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。
Transforms police body camera transcripts into structured 10-section legal summaries with timestamp-cited verbatim statements, constitutional issue spotting, evidence inventory, and probable cause articulation. Maintains strict neutrality for all parties. Use when analyzing BWC footage for discovery, pre-trial prep, or trial. Trigger: body camera, BWC, body worn camera, officer footage, use of force review, incident summary.
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。
Validates and summarizes the four required authorization forms in a personal injury matter (retainer, HIPAA release, insurance authorization, employment record release). Confirms signatures, dates, scope, and completeness to determine readiness for the investigation phase. Use when reviewing client onboarding packets, verifying authorization forms before discovery, or checking HIPAA and record-release compliance.
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 U.S. commercial real estate access and indemnity (right-of-entry) agreements for pre-closing due diligence. Covers license grants, non-invasive vs invasive testing gates, insurance/endorsement requirements, indemnity with discovery carve-outs, restoration and lien remedies, confidentiality, and anti-indemnity guardrails. Trigger: access agreement, right of entry, due diligence access, Phase I/II, invasive testing, pre-PSA site inspection.
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。
OpenLineage, DataHub, Marquez for data lineage tracking and impact analysis. Activate on: data lineage, OpenLineage, DataHub, Marquez, impact analysis, data catalog, column lineage, data discovery. NOT for: data quality validation (use data-quality-guardian), dbt documentation (use dbt-analytics-engineer).
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。
Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP data.
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。
Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2024 bioRxiv; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.
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。
Query BindingDB for measured drug-target binding affinities (Ki, Kd, IC50, EC50). Search by target (UniProt ID), compound (SMILES/name), or pathogen. Essential for drug discovery, lead optimization, polypharmacology analysis, and structure-activity relationship (SAR) studies.
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。
Predict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero. Use when linking distal enhancers to target genes, choosing between contact-aware (ABC, ENCODE-rE2G), accessibility-only (Cicero), and orthogonal (HiChIP H3K27ac, EpiMap) approaches, validating predictions against CRISPRi-FlowFISH gold-standard, or building cell-type-specific regulatory maps for fine-mapping or therapeutic target discovery.
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。
Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
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。
Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.
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。
Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.
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。
Find Amazon Ads search terms ready for exact-match harvesting from auto, broad, phrase, or other discovery campaigns. Use when Codex needs standalone or Rocketcart MCP-aware search-term harvesting: classify terms by harvest readiness, resolve live IDs, choose safe destination campaigns/ad groups, preflight duplicates/current negatives/destination feasibility, decide whether source negatives are justified, execute only explicitly approved rows, and read back/monitor Sponsored Products or Sponsored Brands actions without unsafe negatives, duplicate routing, stale approvals, brand-defense cuts, own-ASIN-defense cuts, launch/rank mistakes, or low-sample overfitting.
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 or resume a deliverable active-outreach workflow across lead discovery, screening, customer intel, and outreach email. Use when an operator or system pipeline needs durable run state, visible intermediate artifacts, evidence gates, report-bound human approval, and a final editable email draft that is never auto-sent.
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。
Find the first batch of foreign-trade prospect companies from public web, LinkedIn, and user-authorized data sources such as customs exports, trade show lists, association directories, CRM/Excel files, or historical customer data, then output a conservative, structured candidate list ready for lead screening.
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 prospect companies from a structured OpenClaw search brief, including public search and user-authorized data sources, then output a conservative candidate list ready for lead screening.
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 B2B leads from Reddit using AI-powered lead scoring via reddapi.dev Leads API. Finds high-intent signals, scores them 0-100, and classifies by lead type (pain_point, solution_request, complaint, feature_request, comparison). Perfect for competitor poaching, pain point discovery, and sales prospecting.
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 for design thinking, or when a product or service problem needs user understanding before solutions: "what do users really need?", "how might we...", "plan a discovery sprint", "validate this concept". Skip when the spec is frozen or the task is code maintenance.
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。
llama.cpp local GGUF inference + HF Hub model discovery.
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。
Reverse engineer and security-test Telegram bots — API analysis, callback interception, exploit discovery, and vulnerability 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。
BluOS CLI (blu) for discovery, playback, grouping.
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。
Expert-level materials informatics covering materials databases, machine learning for property prediction, high-throughput computation, and data-driven materials discovery.
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。
Govern discovery, eligibility, and submission of a plugin or skill to official directories, registries, marketplaces, and curated GitHub lists. Use when preparing or sending plugin listings, marketplace forms, directory PRs, or repository recommendations; require current policy evidence and a final human confirmation before every external submission.
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。