「analysis」の検索結果

Top 5 local competitor analysis — menu, pricing, review, social, and SEO comparison with positioning gap identification

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。

Multi-platform review analysis — pulls Yelp/Google/TripAdvisor reviews, identifies recurring complaints, sentiment patterns, response rate, and rating trajectory

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。

Competitive pricing analysis — compares menu prices against local competitors, identifies underpriced items leaving money on the table and overpriced items hurting sales

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。

Ascend cluster comparison tool. Invoke when user asks to compare two cluster datasets (DB or TEXT), or to generate cluster_analysis_output from raw profiling data via msprof-analyze and then compare.

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。

训练与推理数据不一致的端到端根因分析。当模块映射/值比较不足以定位问题时使用，可追踪首个可信的分歧边界，过滤融合或结构性误报，遵循生产者-消费者链，并生成包含具体假设和证据的根因报告。

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。

执行msProbe数据比对并分析比对结果，定位确定性计算问题首个输入一致输出不一致的API。

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。

Compile, profile, diagnose, optimize, and compare Ascend NPU operators across CANN versions and A2/A3/A5 for Ascend C, CATLASS, Triton-Ascend, TileLang-Ascend, PyPTO, and SHMEM/MC2. Use when an operator already has a runnable implementation and the user asks for msOpProf collection, bottleneck analysis, source-level tuning, or a reproducible before/after performance report. Do not use as the primary workflow for operator creation, migration, or unresolved correctness failures.

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。

对 msMemScope 显存数据做全链路处理：根据用户的显存问题诉求（OOM、显存泄漏、显存占比拆解、Step 间对比等），指导并帮助用户以最合适的 msMemScope 采集配置完成显存数据采集（支持命令行、Python 接口、mstx 打点三种采集方式，覆盖训练、推理 vLLM-Ascend、FSDP、强化学习 verl 等场景）；对已采集的 memscope_dump_*.csv/db 数据做系统性解读与问题诊断（整体显存曲线趋势分析、显存使用大头按模块/组件拆解分析、显存峰值点各模块与流程占比分析，以及对显存泄漏、OOM 等典型问题的根因定位与原因分析）。

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 Ascend NPU computation-side profiling data for single-card runs or a selected rank from multi-card runs. Use this skill when the user asks to diagnose computation bottlenecks, AI Core / AI Vector / AICPU hotspots, dynamic shape overhead, block dim issues, redundant TransData/Transpose/Cast, cross-stream waits, frequency/runtime-state issues, or fusion opportunities.

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。

分布式训练梯度尖刺 (Gradient Spike) 根因定位。基于梯度监控数据 (trend.db/CSV)、 msprobe dump 统计数据，三阶段渐进式从异常坐标定位逐层深入到算子级根因。 当用户明确指明分析梯度尖刺问题时使用此 skill。 即便用户提供以上数据，但未指明分析梯度尖刺问题时，不可使用此skill。

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。

在实现适配器前对候选模型做分析。确定模型实现来源（transformers / 模型目录 / diffusers）、结构特征、内存约束下的逐层量化建议（可选）及 MoE 融合权重风险。适用于用户询问模型适配可行性或做适配前分析时使用。识别为 DiT 扩散模型时，索取推理仓路径后回传 `next_step: model-adapt`，由 orchestrator 委派 `msmodelslim-model-adapt`（DiT 扩展节承接）。

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 Ascend NPU schedule, operator dispatch, operator launch, and Host Bound profiling issues in Ascend profiling data. Use when need to diagnose device Free time, framework/operator dispatch latency, launch latency, PYTORCH_API/CANN_API launch gaps, aclrtSynchronizeStream stalls, task queue behavior, CPU scheduling interference, GC/lock pauses, CPU affinity, or schedule-side optimization actions.

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。

Create high-quality, SEO-optimized content that ranks AND reads like a human wrote it. Performs live SERP gap analysis, writes with anti-AI detection techniques, and adds schema markup. Use when someone needs a blog post, article, SEO page, or wants content that drives search traffic. Triggers on 'SEO content', 'blog post', 'article', 'SERP', 'programmatic SEO', 'content at scale', 'template pages at scale', 'write a post about', 'rank for', or 'search-optimized content'. Two modes: single article or programmatic SEO at scale. Owns programmatic SEO and content-at-scale generation. For a single alternatives or vs/comparison page, see /competitor-alternatives; for a multi-phase page roadmap with a persistent tracker, see /seo-machine.

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。

Optimizes multi-step conversion flows including signup, onboarding, upgrade, and checkout. Maps each step, identifies friction and drop-off risks, then recommends specific copy/UX changes with A/B test plans. Use when someone says 'signup flow', 'onboarding optimization', 'checkout conversion', 'paywall optimization', 'activation rate', 'funnel analysis', 'why are users dropping off', 'registration flow', 'trial conversion', 'free to paid', 'upgrade flow', 'user journey', or wants to improve any multi-step user journey. If they mention steps, screens, or a sequence that leads to signup, payment, or activation, this is the skill. Even casual mentions like 'users aren't finishing signup' or 'our onboarding sucks' should trigger this. Use this instead of page-cro when the problem spans multiple screens rather than a single page.

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。

Research and analyze competitors to find positioning gaps and strategic opportunities. Use this skill whenever the user mentions competitors, competitive analysis, competitor teardown, market landscape, 'who else does this', 'how are we different', or competitor research. Also trigger when the user is entering a new market, when positioning feels weak or generic, when preparing for a launch, when any downstream skill needs competitors.md but it doesn't exist, or when the user asks about differentiation or market gaps. Even if the user just names a competitor casually ('what does X do?'), this skill likely applies. Three modes: Quick Scan, Deep Teardown, Gap Finder.

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。

Friendly SEO coach mode for the mktg + OpenSEO stack. Use this skill when the user is new to SEO, unsure which SEO workflow to run, asks "what does OpenSEO do", wants strategy explained in plain language, or needs help choosing between keyword research, clustering, competitive analysis, and link prospecting. Triggers: "seo coach", "new to seo", "explain openseo", "what seo should i do", "seo strategy help".

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。

Research companies, competitors, funding, news, leadership, and market context with Exa Agent and advanced search. Use when researching companies, competitor analysis, market research, or building company lists. Writes findings the caller can fold into brand/competitors.md or brand/landscape.md. Prefer this over ad-hoc web search for company deep dives. Distinct from competitive-intel (full brand competitive file methodology) - this skill is the Exa research engine those foundation skills should call.

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。

Map who is winning an SEO market with measured data — recurring SERP domains, organic footprints, winning content themes, backlink authority, and the gaps worth attacking. Use this skill for market-level questions ("who ranks for X", "how competitive is this space", "where are the SEO openings") before committing to keyword targets or content themes. For one named competitor, use openseo-competitor-analysis instead. Triggers: "competitive landscape seo", "who ranks for", "seo market map", "how competitive is", "serp competitors".

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。

Deep-dive ONE competitor's organic footprint — exact ranking keywords and URLs, content themes, backlink profile, and exploitable gaps — with findings written into brand/competitors.md. Use this skill when the user names a competitor and wants to know what to learn from them, counter, or outrank, including head-to-head comparisons against the user's own domain. For market-level mapping first, use openseo-competitive-landscape. Triggers: "analyze competitor", "competitor keywords", "competitor backlinks", "beat <competitor>", "competitor seo teardown".

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。

Analyzes Perfetto traces to find the root cause of latency, memory, or jank issues in Android apps. Use when the user provides a Perfetto trace file and asks any question, ongoing investigation, or open-ended request to analyze its contents.

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 the open-source free `Roslynator` analyzer packages and optional CLI for .NET. Use when a repo wants broad C# static analysis, auto-fix flows, dead-code detection, optional CLI checks, or extra rules beyond the SDK analyzers.

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 whenever the user mentions Betaflight, FPV drone firmware, flight-controller config, PID/filter/rates tuning, or blackbox log analysis — or shares a Betaflight artifact: a CLI diff/dump (lines like 'diff all', 'set ', 'feature ', 'resource ') or a .bbl/.bfl blackbox log, even when not named as such — or runs a chirp tuning session via Sweep Studio / FPVLogForge (a chirp log ID to analyse, 'analyse log', 'résultat chirp', iterative Bode/step/Ms tuning). Covers flight symptoms (oscillations, wobble, propwash, jello, hot motors, drift), motor/ESC and RX/ELRS/CRSF setup, builds from 3" to 10" (cinewhoop, tinywhoop, longrange, X-class), version migrations (4.4 → 4.5 → 4.6), and configuring a new drone from scratch (setup wizard). Trigger even when phrased casually ("mon drone wobble", "PID help", "config FC") — under-triggering is worse than over-triggering.

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 AI image processing pipelines for generation and analysis. TRIGGERS - Use when user needs help with ai-image-pipeline related tasks.

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 AI patent analysis systems. TRIGGERS - Use when user needs help with ai-patent-analyzer related tasks.

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。