「core」の検索結果

Configure the studio, brand, and generation tools. Use on a missing-config report, or when the user says "set up manticore", "change my tools", or "update my studio".

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。

End-to-end Android indie idea workflow — feature-build phase only (no monetization). Phased — discover (if no idea) → generate 2 candidates → refine scope (offline/online, sharing, MVP vs full, core-value features) → risk/reward/tradeoff analysis when scoping down → emit idea brief. Use for greenfield app concepts, new feature ideation, idea discovery, or pre-design discovery before writing a design document. Triggers — new app idea, feature concept, indie dev brainstorm, validate idea, refine idea, what should I build, find an app idea, idea pipeline, I have no idea, help me find an app idea, scope down, MVP scoping, core value features.

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 Self-Rewriting Core: AST analyze, patch, commit.

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Expert en customer success avancé (onboarding, adoption, expansion, QBRs, NPS, health scores)

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。

Churn prevention specialist — Early warning signals, retention campaigns, win-back, health scores

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Expert en prévention du churn avancé (early warning, health scores, win-back campaigns, predictive)

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 en développement AR/VR (ARKit, ARCore, WebXR, Unity XR, spatial computing)

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Expert en audit d'accessibilité (WCAG 2.2, axe-core, Lighthouse, screen readers, keyboard navigation)

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Expert en agent loops (ARIS, Ralph, recherche autonome, build-score-budget, guardrails)

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Accessibility auditor v3 — WCAG 2.2, axe-core, Lighthouse, manual testing, RGAA

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。

Implement computer vision features including text recognition (OCR), face detection, barcode scanning, image segmentation, object tracking, and document scanning in iOS apps. Covers both the modern Swift-native Vision API (iOS 16+) and legacy VNRequest patterns, VisionKit DataScannerViewController for live camera scanning, and VNCoreMLRequest for custom model inference. Use when adding OCR, barcode scanning, face detection, or custom Core ML model inference with Vision.

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Scan, connect, and communicate with Bluetooth Low Energy peripherals and publish local peripheral services using Core Bluetooth. Use when implementing BLE central or peripheral roles, discovering services and characteristics, reading and writing characteristic values, subscribing to notifications, configuring background BLE modes, restoring state after app relaunch, or working with CBCentralManager, CBPeripheral, CBPeripheralManager, CBService, CBCharacteristic, CBUUID, or Bluetooth Low Energy workflows.

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Access accelerometer, gyroscope, magnetometer, pedometer, and activity-recognition data using CoreMotion. Use when reading device sensor data, counting steps, detecting user activity (walking/running/driving), tracking altitude changes, or implementing motion-based interactions in iOS/watchOS apps.

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。

Read and write NFC tags using CoreNFC. Use when scanning NDEF tags, reading ISO7816/ISO15693/FeliCa/MIFARE tags, writing NDEF messages, handling NFC session lifecycle, configuring NFC entitlements, or implementing background tag reading in iOS apps.

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Expert Core Data guidance (iOS/macOS): stack setup, fetch requests & NSFetchedResultsController, saving/merge conflicts, threading & Swift Concurrency, batch operations & persistent history, migrations, performance, and NSPersistentCloudKitContainer/CloudKit sync.

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Core Web Vitals budgets: production-level LCP, CLS, INP, GPU scheduling. Use when implementing, reviewing or testing core web vitals budgets for React, Vite, Next.js or Perfect_AI projects.

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Shared foundation for all human-voice writing skills. Load before any profession-specific skill. Contains: burstiness principle, perplexity principle, soul injection techniques, community-discovered AI patterns with sources, additional core patterns, banned AI vocabulary, and scoring rubric.

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Convergence loop that iteratively improves work until quality thresholds are met. Scores, diagnoses specific weaknesses, rewrites, re-scores, and repeats until all dimensions reach 8/10 or diminishing returns are detected. Use when you want to refine or iterate on work, after the analyst gives a REVISE verdict, or when output quality is below your bar. Part of the architect-system loop. Outputs to system/refinery-log.md.

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Convergence loop that iteratively improves work until quality thresholds are met. Use when: (1) "refine this", "make this better", "iterate on this", (2) After /analyst gives a REVISE verdict, (3) Output quality is below 8/10, (4) "run the refinery loop on this". Reads analyst reviews from system/reviews/. Generates, scores, diagnoses, rewrites, re-scores. Stops when all dimensions >= 8/10 or diminishing returns detected. Outputs to system/refinery-log.md.

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Core component library and design system patterns. Use when building UI, using design tokens, or working with the component library.

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bu skill instructs security practitioners on Dağıt:ing Microsoft Defender for Cloud as a cloud-native application protection platform for Azure, multi-cloud, and hybrid environments. It covers enabling Defender plans for servers, containers, storage, and databases, configuring security recommendations, managing Secure Score, and integrating with the unified Defender portal for centralized threat 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。

Review board (Busabase App-in-Skill) that runs a fixed suite of mock test cases against a baseline vs candidate agent version and surfaces rubric-scored regressions before a release. Use when the user invokes $kelly-agent-eval or /kelly-agent-eval, wants to review agent-version regressions, compare baseline vs candidate quality, triage a release, or record a release approve/block decision. Deterministic mock rubric scores only — not a real LLM-judge call, and it never deploys anything.

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。

Outbound email-marketing desk (Busabase App-in-Skill) for building segments, drafting campaigns, newsletters, and sequences, running pre-send deliverability and subject-line QA, and approving every send before it is scheduled. Structured around the SEND discipline — Setup, Engage, Nurture, Deliver — with an email-quality-auditor gate (EQS score + SHIP/FIX/BLOCK verdict). Use when the user invokes $kelly-campaigns or /kelly-campaigns, or mentions email marketing, campaigns, newsletters, drip/welcome/win-back sequences, broadcasts, segments, subject-line A/B tests, deliverability (SPF/DKIM/DMARC/spam score/inbox placement), or wants to review and approve marketing email before it is sent. This is OUTBOUND marketing to a subscriber list, distinct from kelly-email inbox triage (incoming mail). 出站邮件营销：策划分群、起草营销活动 / 新闻邮件 / 邮件序列，发送前做可送达性与主题行质检，人工审批后再排期发送。

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Focused Signals scout for PostHog projects running Replay Vision scanners — the standing LLM probes that watch session recordings and write `$recording_observed` events. Watches two promises: that enabled scanners are actually observing (throughput / success-rate cliffs, exhausted quota — a silent watch gap), and that what the scanners see in aggregate gets surfaced (a monitor's `yes`-rate or a scorer's score stepping away from its own baseline, a classifier tag or a recurring summarizer theme concentrating across many sessions). It is the agentic pull complement to the per-session push path: scanners with `emits_signals` already emit one signal per session into this same inbox, so this scout never repeats them — it adds the cross-session shape the per-session probe can't see. Emits findings only when they clear the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet.

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。