9.4만건 · 관련도순
Check HTML for meta refresh redirects that can interrupt reading and confuse users. Suggest server-side redirects or clear links users choose themselves, with guidance for checking the resulting behavior using accessibility tools or assistive technology.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Review Apache ShardingSphere pull requests or authorized downstream changes using repository evidence. Assess code correctness, merge readiness, or CI failures, then produce consolidated findings or a ready-to-copy reply to a review discussion.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Review changes of 1,000 lines or more by dividing work across files, focused areas, and commits. Combine several review methods, check consistency across subsystems, verify bug fixes, and report validated findings alongside a checklist showing review coverage.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. If you're thinking relationally, you're thinking wrong. 2025 lesson: Firestore pricing can surprise you. Reads are cheap until they're not. A poorly designed listener can cost more than a dedicated database. Plan your data model for your query patterns, not your data relationships. Use when "firebase, firestore, firebase auth, cloud functions, firebase storage, realtime database, firebase hosting, firebase emulator, security rules, firebase admin, firebase, firestore, cloud-functions, serverless, backend, realtime, authentication, google-cloud" mentioned.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Plan press outreach for software products, develop story angles, and prepare pitches, press materials, and podcast briefs. The skill also guides crisis communications, including initial statements and responses to breaches or outages.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Develop a research question, search and verify literature, and combine findings into an academic report. Modes also support guided research discussions, claim checking, paper comparisons, and systematic reviews with optional meta-analysis, which statistically combines study results.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Prepare a Cherry Studio release by checking changes against the published version, writing English and Chinese release notes, updating version metadata, and creating a release branch after review to start the build workflow.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Prepare raw credit data for pre-loan modeling by checking data quality and screening variables. Review missing values, predictive usefulness, stability, noise, and correlation, then export an Excel report with organization-level statistics and cleaning results.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Prepare a professional reference list for job applications, choosing people who can discuss your work. Draft permission requests and briefing materials, organize contact details, and prepare for questions employers may ask your references.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Adapt machine learning training to run across multiple GPUs or machines with Ray Train. Covers changes to existing code, comparing training settings with Ray Tune, and saving checkpoints so training can resume after failures.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build 3D scenes in React from JSON specifications using json-render. The skill covers shapes, lighting, model loading, materials, cameras, and view controls, plus connecting component definitions to their rendering implementations.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build 3D browser games and interactive scenes inside React apps with React Three Fiber. Organize gameplay logic, coordinate scene and interface state, and connect the 3D experience with standard web menus, settings, and status displays.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Audit whether a paper's EVALUATION DESIGN actually measures what it claims and whether its reporting is complete — the validity layer family D (experiment-forensics) cannot reach. Three patterns: train/test leakage means the reported score may not measure generalization (HP-EVAL-LEAKAGE — adopts the Kapoor & Narayanan 8-type / 3-category leakage taxonomy; the illegitimate-proxy / sampling-bias / pretraining-contamination subtypes hand off as needs_external_check, naming but NEVER running Oren-2023 exchangeability / Shi-2023 Min-K% / Golchin-2023 Time-Travel / BIG-bench canary); a load-bearing LLM judge is conflicted (same model/family as a compared system) or unvalidated (no human-agreement, no bias control) (HP-JUDGE-VALIDITY); a declared condition/metric is dropped or switched to favor the method, or 'best' is chosen with no held-out set (HP-SELECTIVE-REPORTING). Verdict-bearing at L0/L1 from the DESCRIBED protocol — NOT repo-gated like experiment-forensics; L2 only CONFIRMS against split/preprocessing/result files. A fresh cross-model reviewer (gpt-5.6-sol xhigh, read-only, fresh thread per pass) PROPOSES findings, each span-anchored to a ledger claim_id; tools/adjudicate_findings.py DECIDES the verdict. Leakage and under-reporting are usually HONEST methodological errors — every finding describes a discrepancy to CHECK, never an accusation. An LLM generating GROUND-TRUTH labels is HP-FAKE-GT (experiment-forensics) — routed there, not here. Emits eval-design-forensics.findings.json; computes NO verdict. Detect-only. Triggers: "eval design audit", "evaluation validity", "train/test leakage", "data leakage", "is the score measuring generalization", "LLM judge bias", "is the judge validated", "selective reporting", "cherry-picked results", "评估设计审计", "评测有效性", "数据泄漏", "训练测试集泄漏", "裁判模型有没有验证", "选择性报告".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Read current or previous Muse Code session logs to recover context, review decisions and tool results, or reconstruct lost files from recorded changes. It also helps locate the relevant session for a workspace.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Assess potential data breach impact by reviewing sensitive data and its movement through a codebase. Produce an inventory, exposure rankings, financial estimates, and prioritized safeguards, distinguishing legal source figures from planning estimates.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Retrieve current Azure retail prices and estimate monthly or annual costs by service, region, and configuration. Compare payment options and calculate Copilot Studio credit usage and estimated costs from expected agent activity.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Prevent and investigate excessive rendering in Lite React screens. It guides data transformations, context use, and store subscriptions, then checks compiler output and measures rendering time before and after changes to verify their effect.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Turn penetration test and red team results into reports for executives and technical teams. Structure findings, explain severity scores and business impact, organize evidence, and document remediation steps and retest plans.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Investigate how credentials can be exposed in CI/CD, the systems that build and deploy software. Covers environment variables, logs, credential stores, cloud trust settings, and runner tokens, with methods to assess access scope and defensive controls.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build the effects of a fire skill as one visual language in Three.js. Flames that read as fire, not as orange fog or cones: ray-marched flame volumes whose turbulence rises with buoyancy (slow at the root, accelerating and stretching as it climbs) instead of scrolling, a temperature ramp from a white-hot core a little above the fuel through yellow and orange to deep red tips, broad brighter licks inside, walls of fire broken into clumps of separate tongues of very different heights with notches between them and licks that detach and go out, a fire whirl wound in helical sheets with a waist and a blue root; charcoal smoke drawn premultiplied over the frame and lit only by the fire (cauliflower billows for a burst, a thin streaked curtain off a grass-fire front, fibrous wisps off small fires, ragged hot cracks inside a burst's smoke); embers and sparks that drift on a curl field, cool from white through orange to red and fall as ash; heat haze as refraction; firelight shared with the world; a world-space heat map that makes the ground's needles smoulder as hairlines and its pockets breathe; and gentle ink impact frames limited to three flashes a second. Use for fire or flame skills, fireballs, fire waves or breath, rings of fire, fire tornadoes or whirls, burning ground, wildfire fronts, smoke columns, embers, smouldering aftermath, "fire and smoke", "realistic fire", "flame thrower", "inferno", "burning field" or "skill effects only". Includes a reusable module and a five-beat demo on a scanned CC0 burned-ground floor with failure-mode switches.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Walmart product detail page extractor: given a walmart.com product URL (walmart.com/ip/...), extract full product data including itemId, title, brand, model, UPC, price, wasPrice, currency, availability, category path, seller info, all images, shortDescription, longDescription, product highlights, full specifications as key-value map, color/size variants with item IDs, fulfillment options (shipping/pickup/delivery with dates), return policy, and review summary with rating breakdown. Use when user mentions walmart product detail, walmart item page, walmart product page, scrape walmart product, extract walmart item, walmart product data, walmart item details, walmart product info, walmart product scraper, walmart item scraper, walmart product URL, walmart ip URL, walmart.com/ip, walmart specifications, walmart product specs, walmart product images, walmart variants, walmart color options, walmart size options, walmart seller info, walmart return policy, walmart fulfillment options, walmart shipping info, walmart availability, walmart product enrichment. Also applies to enriching a list of walmart product URLs with full details, monitoring walmart product price and availability changes, building a walmart product catalog, competitive product research on walmart, and batch collection of full product data from walmart item IDs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
freee API 명세와 절차 예시로 경비, 거래, 근태, 청구서와 공수 데이터의 조회 및 갱신을 지원합니다. 연결 설정과 인증 오류 대응도 안내합니다.
Turn Strix vulnerability findings into focused code fixes, prioritized by severity. Address root causes, rerun security scans and original exploit examples, and report the changes and verification results for each issue.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.