「nif」の検索結果

Publish crates to crates.io with pre-flight checks

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。

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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 task needs the judgment of a Customs and Border Protection officer — scoring a shipment or traveler for secondary-inspection referral, evaluating a manifest discrepancy for contraband risk, deciding whether a traveler is admissible under immigration law, structuring a seizure or penalty referral, or triaging a primary-inspection queue under time pressure.

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 task needs the judgment of an Administrative Law Judge, Adjudicator, or Hearing Officer — applying a mandatory sequential/structured evaluation framework in required order, weighing conflicting medical or vocational opinion evidence using specific regulatory factors, writing findings that explicitly address significant contrary evidence in the record, drafting a credibility/consistency finding tied to specific record citations, or checking whether a draft decision would survive substantial-evidence review.

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 ENCODE uniform analysis pipelines, generate user-specific Nextflow/WDL pipelines, manage compute resources, and integrate with cloud platforms. Use when the user wants to understand ENCODE pipelines, run pipelines on their own data, generate custom Nextflow workflows from ENCODE pipeline code, check compute requirements (CPU/GPU/memory), run pipelines in background, or integrate with Google Cloud, AWS, or other cloud platforms. Also use when the user asks about ENCODE pipeline outputs, processing standards, software versions, or wants to replicate ENCODE processing. Covers local execution, HPC, and cloud deployment with resource-aware scheduling. Use this skill for ANY pipeline execution, workflow generation, or compute resource management task involving ENCODE 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。

Scaffold or migrate a repository onto release-please. Generates release-please-config.json, .release-please-manifest.json, and a release-please.yml workflow, plus an opt-in menu of tag-keyed deploy/publish templates (Docker/ECR matrix, frontend host deploy, npm OIDC publish, GitHub Release asset, Fly.io deploy, generic). Supports monorepo (mutual exclude-paths matrix), single-package, and mixed-language (node/simple/python) repos. Use when user runs /release-please-setup, mentions "release please", "set up release please", "automate releases", "conventional-commit releases", "monorepo release automation", or "migrate to release-please".

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 brand icons as SVG and produce all platform assets including favicon package (ICO, SVG with dark mode, apple-touch-icon), PWA manifest icons, and mobile app icons. Use when user runs /icon-forge, requests "brand icon", "favicon generation", "app icon", or "svg logo" for a project.

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。

Show a domain's Domain Rating trend over time from Ahrefs. Reveals DR growth, drops, and significant changes. Use when user says "DR history", "domain rating history", "DR trend", "domain rating over time", or "DR changes".

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。

Guidance for Tauri v2 dialog plugin with native dialogs and unified API design.

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 deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster management.

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。

Creates Dockerfiles, configures CI/CD pipelines, writes Kubernetes manifests, and generates Terraform/Pulumi infrastructure templates. Handles deployment automation, GitOps configuration, incident response runbooks, and internal developer platform tooling. Use when setting up CI/CD pipelines, containerizing applications, managing infrastructure as code, deploying to Kubernetes clusters, configuring cloud platforms, automating releases, or responding to production incidents. Invoke for pipelines, Docker, Kubernetes, GitOps, Terraform, GitHub Actions, on-call, or platform engineering.

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-reference design audit -- validates consistency across spec, schematics, BOM, pin maps, and PCB layout. Catches disagreements before fabrication. Run after any significant design change.

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。

Choosing colormaps scientifically — perceptual uniformity, color-vision deficiency, and matching map to data type.

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。

Argo CD guidance — GitOps workflows, Application manifests, sync strategies, AppProjects, and multi-cluster 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。

Generate production-grade Kubernetes manifests — Deployments with probes and security contexts, Services, Ingress with TLS, HPA, PDB, NetworkPolicy, ConfigMaps, Secrets — with optional Helm charts, Kustomize overlays, Istio mesh, and ArgoCD GitOps

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。

Evaluate survey data pipelines and research methodology. Analyzes response bias detection (speeders, straight-liners, bots), statistical significance testing (t-test, chi-square, ANOVA with Bonferroni correction), sentiment and theme extraction from open-ended responses.

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。

Runs a 4-phase compliance pipeline: security scan, GDPR audit, dependency vulnerability check, and penetration test, producing a unified pass/fail compliance report. Triggers: on: "compliance check", "compliance gate", "run compliance", "pre-release compliance", "security and 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。

Monitor federal grant opportunities across Grants.gov (Simpler.grants.gov is the modern UX), SAM.gov assistance listings (the post-CFDA replacement that preserves CFDA program numbers), and direct agency portals — NIH RePORTER + NIH Guide, NSF Funding, DOE OSTI, USDA NIFA, EPA Grants.

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 grant management and sponsored research operations including proposal lifecycle tracking, pre-award routing and budget development, post-award expenditure monitoring and burn rate analysis, 2 CFR 200 Uniform Guidance cost allowability 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。

Write long-form thought leadership articles, opinion pieces, industry POV essays, and CEO/founder bylines using the Made to Stick SUCCESs framework (Chip and Dan Heath). Use when the user asks for a long-form article, executive byline, opinion piece, industry POV, manifesto, "explain our point of view on X", or wants to publish an authority-building piece (1200-2500 words). Reads brand voice and positioning from knowledge/. For a short-form post, see linkedin-post. For the newsletter, see newsletter-writer. For improving an existing draft, see copy-review.

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。

Transform reference photographs and visually dense images into sparse, recognizable, high-saturation flat-vector-style illustrations through semantic compression rather than literal tracing. Use when the user asks for photo-to-flat illustration, photo-to-vector-style redraw, 照片转扁平插画, 无渐变高饱和插画, iconification, visual simplification, composition-preserving abstraction, a consistent minimal illustration set, or revisions that remove gradients, glow, texture, blur, clutter, text, logos, numbers, or UI. Default to human-perceived semantic complexity 6 out of 10 or lower, fixed-HSB solid fills, crisp boundaries, and no gradients or light-halo effects.

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。

Design and evaluate paid-ad experiments with hypotheses, randomization units, sample-size and duration assumptions, guardrails, platform experiment tools, analysis, and decision rules. Use for A/B test, split test, experiment design, hypothesis, statistical significance, sample size, test duration, or experiment readout.

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。

Validate Claude Ads contracts, scoring inputs, run bundles, capabilities, source freshness, safety, installation, uninstall, or release readiness. Use for ads validate, ads status, ads next, stale claims with missing tool access, maturity checks, ownership-manifest uninstall, preserving unrelated ads-* skills, checksum verification, preflight, QA, or release audits. Missing access must demote stale evidence for the run and block dependent release-current claims before recovery guidance.

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。

Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.

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。