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概要と使いどころ
Deep Single-Candidate Scoring — evaluate one candidate across 5 dimensions (skills match, experience relevance, culture fit signals, growth potential, red flags) with final 0-100 score and hire/no-hire signal
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。
Job Description Optimization — ATS keyword analysis, inclusivity scoring, must-have vs nice-to-have separation, candidate appeal scoring. Rewrites the JD.
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 building, migrating, or debugging Agent Evals on Inngest: scoring AI agent or workflow outcomes, deferred scorers, sessions, traces, step experiments, experiment variant attribution, Insights queries, or production eval loops for prompts, models, tools, providers, and agent behavior. Covers TypeScript SDK v4 scoring beta APIs, `scoreMiddleware`, `step.score`, `inngest.score`, `createScorer`, `defer`, `group.experiment`, `experimentRef`, `meta.sessions`, and when to use durable workflow primitives for outcome-based evaluation.
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。
Lead Qualification And Scoring Specialist. Use to define ICP filters, score inbound and outbound leads, and improve pipeline focus for a founder-led sales motion.
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。
"Build credit scoring models to predict default probability from borrower characteristics. Use this skill when the user needs to assess creditworthiness, build a credit scorecard, or evaluate lending risk — even if they say 'predict default risk', 'credit scoring', or 'loan approval model'.".
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 contracts with clause-by-clause risk scoring, market benchmarks, negotiability ratings, and redline suggestions. Use when the user pastes an NDA, SaaS/MSA, M&A LOI, or payment agreement and wants a Contract Safety Score, CUAD-based risk breakdown, or /review as [position] analysis.
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。
Email marketing operations and automation for B2B SaaS. Use this skill for newsletter strategy, email automation sequences, lifecycle campaigns, nurture workflows, onboarding sequences, deliverability optimization, email copywriting, lead scoring, marketing automation platform setup, and cold-email sending infrastructure — secondary sending domains, SPF/DKIM/DMARC, and domain warmup — plus the contact budget: a cross-channel frequency cap across every sender (marketing, sales sequences, customer success, in-app). Also triggers on: email, newsletter, drip campaign, lifecycle, nurture, onboarding sequence, deliverability, email automation, lead scoring, marketing automation, our emails are going to spam, SPF, DKIM, DMARC, sender reputation, sending domain, cold email domains, domain warmup, mailbox setup, blacklist, bounce rate, BIMI, brand logo in inbox, VMC, Verified Mark Certificate, Common Mark Certificate, transactional email, password reset emails going to spam, frequency cap, email fatigue, customers get too many emails, too many messages, sales and marketing both emailing the same person, communication limits, send frequency safeguard, global frequency capping, quiet period, message precedence.
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。
Audit workplace risk scoring systems and occupational safety programs -- evaluate job hazard analysis (JHA/JSA) methodology and task-level hazard identification, risk matrix calibration for likelihood and consequence scales, exposure assessment accuracy for chemical, noise, vibration.
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。
Analyze behavioral segmentation systems for RFM scoring, cohort tracking, churn propensity, engagement scoring, persona clustering, and journey mapping using behavioral economics frameworks..
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。
Audit and score blog posts on a 5-category 100-point scoring system covering content quality, SEO optimization, E-E-A-T signals, technical elements, and AI citation readiness. Includes advisory editorial style diagnostics (sentence-length variation, configured phrase lists, vocabulary sampling) that never infer authorship or affect scoring. Supports export formats (markdown, JSON, table) and batch analysis with sorting. Generates prioritized recommendations (Critical/High/Medium/Low) with specific fixes. Works with any format (MDX, markdown, HTML, URL). Use when user says "analyze blog", "audit blog", "blog score", "check blog quality", "blog review", "rate this blog", "blog health 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。
Use this skill when designing lead nurture journeys in MCAE (Account Engagement / Pardot) Engagement Studio — mapping content to funnel stages (Awareness, Consideration, Decision), behavioral trigger rules, branching program paths, and MQL handoff criteria to Sales. NOT for building a journey in Marketing Cloud Journey Builder — use admin/journey-builder-administration. NOT for the scoring and grading model behind MQL — use admin/mcae-lead-scoring-and-grading.
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 scoring a list of business or solution requirements against the *actual* capabilities of a specific Salesforce org so each row can be classified Standard / Configuration / Low-Code / Custom / Unfit, given an effort tier (S/M/L/XL), a risk tag, and an AppExchange suggestion when applicable. Trigger keywords: fit gap salesforce requirements, score requirements against salesforce capabilities, salesforce capability matrix, classify requirement as standard config custom, fit-gap effort tier, AppExchange alternative for requirement. NOT for requirements elicitation (use admin/requirements-gathering-for-sf). NOT for architecture decisions on the GAP rows (use architect/solution-design-patterns and standards/decision-trees/). NOT for license or edition selection (use architect/license-optimization-strategy and architect/org-edition-and-feature-licensing). NOT for OmniStudio-specific fit-gap (use architect/omnistudio-vs-standard-decision).
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 an admin needs to create an Einstein Discovery story in CRM Analytics Studio, configure prediction definitions, deploy writeback fields, set up what-if analysis, or manage model refresh and activation. Trigger keywords: Einstein Discovery story, prediction definition, writeback field, CRM Analytics Studio, model refresh, what-if analysis, bulk scoring, prediction field, 1OR prefix. NOT for the Einstein Discovery Flow action or model-health monitoring in Model Manager — use admin/einstein-discovery-deployment. NOT for Einstein Prediction Builder, a separate product needing no CRM Analytics license — use agentforce/einstein-prediction-builder. NOT for programmatic scoring through the Connect REST API — use agentforce/einstein-discovery-development.
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 deploying a trained Einstein Discovery model to production records declaratively — activating a prediction definition, mapping output fields to page layouts, adding the Einstein Discovery Action to a Flow, running bulk predict jobs, and monitoring model health via Model Manager UI. Trigger keywords: prediction definition activation, bulk predict job, Einstein Discovery Flow action, Model Manager, prediction field mapping, model refresh activation, scoring job, Einstein Discovery recommendations on record. NOT for authoring the story in CRM Analytics Studio — use admin/einstein-discovery-setup. NOT for programmatic scoring through the API — use agentforce/einstein-discovery-development.
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。
AI-powered conversion rate optimization: landing page audits, CRO scoring, survey segmentation, and lead magnet generation. Use when asked to audit a landing page, run a CRO analysis, segment survey responses, or generate lead magnets. For content quality scoring see content-ops.
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。
Ticket/PRD intake: product area classification, completeness scoring, RCA, technical assessment. Works with Jira (via mk:jira-issue / jira-as), Linear (via MCP), GitHub (via gh CLI), or manual paste. Triggers: 'analyze ticket', 'intake PRD', 'triage issue', 'classify ticket', 'check ticket'.
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。
Ranks skill matches by fit, performance history, and contextual relevance. Applies multi-factor scoring including success rate, resource usage, and task alignment. Activate on 'rank skills', 'best skill for', 'skill ranking', 'compare skills', 'optimal skill'. NOT for semantic matching (use dag-semantic-matcher) or skill catalog (use dag-skill-registry).
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 novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.
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 pooled sgRNA libraries for CRISPR knockout, interference (CRISPRi), activation (CRISPRa), Cas12a multiplex, base-editor, and prime-editor screens. Covers on-target scoring (Rule Set 2, Azimuth, DeepSpCas9, CRISPRon), off-target scoring (CFD, MIT), TSS-relative positioning for CRISPRi/a (Horlbeck, Dolcetto, Calabrese), PAM-variant chemistries, control-guide composition, oligo cloning architecture, and library QC. Use when choosing a genome-wide library (GeCKOv2 vs Avana vs Brunello vs TKOv3 vs Inzolia), designing a focused or paralog-focused custom library, picking CRISPRi vs CRISPRa TSS windows, deciding control-guide proportions, or diagnosing library skew and dropout in a freshly cloned pool.
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。
Classify constitutional (germline) copy number variants for clinical reporting using the 2019 ACMG/ClinGen technical standards points-based framework, with ClassifyCNV and AnnotSV for semi-automated scoring. Covers the separate copy-number-loss and copy-number-gain rubrics, the five-tier classification, ClinGen haploinsufficiency/triplosensitivity and dosage-sensitive regions, de novo and segregation evidence, and population-frequency benign evidence. Use when assigning pathogenic/likely-pathogenic/VUS/likely-benign/benign to a constitutional CNV, scoring a CNV against ACMG/ClinGen criteria, or distinguishing the automatable evidence from the case-specific evidence requiring manual input.
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。
Decide when to order coronary artery calcium (CAC) scoring in a primary-prevention patient and interpret the result per the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers the Class 1 indication (men ≥40 / women ≥45, borderline / intermediate PREVENT-ASCVD risk, uncertainty about LLT), CAC score interpretation (0, 1–99, 100–299, ≥300, ≥1000), how CAC modifies LDL and non-HDL goals, when to repeat CAC, and pitfalls (incidental CAC on non-cardiac CT, radiation, cost). Use when a clinician asks should I order a CAC score, CAC indications, what does CAC 150 mean, treatment goals with CAC score, repeat CAC frequency, CAC in a smoker, CAC vs CCTA, is CAC useful in intermediate risk. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.
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 Clay platform consultant for B2B data enrichment and workflow automation. Use when the user asks about Clay tables, waterfall enrichment, Clay credits, Clay AI columns, Claygent, enrichment workflows, Clay integrations, Clay exports, Clay table design, lead scoring in Clay, or building data pipelines in Clay. Also triggers on "Clay table", "enrichment waterfall", "Clay credits", "Claygent", "Clay AI column", "Clay export", "Clay providers", "enrich in Clay", "Clay column", "Clay formulas", "find emails", "email waterfall", "phone waterfall", "lead scoring", "Clay debugging", "Clay troubleshoot". Do NOT use for general CRM questions without Clay context, cold email copy (use cold-email-copy-playbook), or signal routing (use buying-window-signal-workflow).
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。
Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows. Use when building clinical decision support — drug interaction checks, dose validation, clinical scoring, or alert severity.
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。
日本語の文書を、読み手が見つけ・理解し・使えるように、新規に書く、書き直す、添削する、評価する。レポート、提案書、手順書、設計書、メール、社内文書、AI生成文が対象。「分かりやすく書いて」「手順書を書いて」「書き直して」「読みやすくして」「添削して」「分かりにくい所を教えて」「点数をつけて」「やさしい日本語にして」「ASD-STE100の日本語版のように」などの依頼で、標準名を挙げていなくても使う。Use when writing, rewriting, proofreading, or scoring Japanese prose for clarity and plain language.