「analysis」の検索結果

Multi-platform review aggregation and thematic analysis for any business

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。

Reputation trajectory analysis with inflection point detection and trend forecasting

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 emotional sentiment analysis beyond positive/negative classification

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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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 the user needs to find, prioritize, or engage B2B prospects — defining an ICP, tiering accounts, building or enriching lists, reading buying signals, designing multi-channel cadences, cold calling, LinkedIn outreach, routing inbound leads, or diagnosing weak pipeline generation. Also for live prospecting coaching. Not for closing (use sales-skill), copy (use copywriter-skill), or CAC analysis (use channel-expert).

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 SaaS founder is deciding on or building a product-led growth motion — assessing PLG readiness, choosing freemium vs free trial vs reverse trial, defining activation and PQLs, designing self-serve onboarding and conversion triggers, building viral loops, or setting up PLG metrics (NRG, activation rate, TTV, NDR, CAC payback) and cohort analysis. Also for hybrid product-led-sales design and PLG-vs-sales-led GTM decisions. Not for paid acquisition channel mix (use channel-expert) or the mechanics of price points and tiers (use pricing).

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 the user wants to get found in Google or AI engines (ChatGPT, Perplexity, AI Overviews) — keyword and content strategy, technical or content SEO audits, schema markup, link building, topical clustering, E-E-A-T, AI citation (AEO), or deciding whether SEO is even the right channel for their startup. Calibrated for early-stage, low-authority sites. Not for paid acquisition or channel-mix/CAC analysis (use channel-expert), or writing the page copy itself (use copywriter-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。

Use when the user needs to scope, write, or audit a product spec — a PRD, feature spec, user stories, acceptance criteria, or a "spec this out"/"break this into stories"/"definition of done" request — or wants an existing spec reviewed for gaps and anti-patterns. Triggers whenever a feature idea needs to become structured requirements that align a team on what to build. For the analytics behind success metrics, use data-analysis; for the technical design, use software-architect.

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 the user needs to design, run, or audit product or GTM analytics — metric hierarchies and north stars, funnels, cohort retention, churn, pipeline velocity, forecasting, lead scoring, NRR, A/B tests, or analytical SQL — or uploads a dataset to analyze. Triggers on questions like "why did activation drop", "is this metric meaningful", "review my dashboard", or "what should I measure". For writing the spec that defines a feature's success metrics, use product-spec.

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。

Comprehensive primary skill for agents working with Weights & Biases. Covers both the W&B SDK (training runs, metrics, artifacts, sweeps) and the Weave SDK (GenAI traces, evaluations, scorers). Includes helper libraries, gotcha tables, and data analysis patterns. Use this skill whenever the user asks about W&B runs, Weave traces, evaluations, training metrics, loss curves, model comparisons, or any Weights & Biases data — even if they don't say "W&B" explicitly.

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。

Maintain and publish the advisor-owned current research state, durable research-ideas syntheses, and dataset analysis. Use when evidence or human guidance changes the research focus or direction, durable research ideas should be recorded, or dataset understanding 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。

Audit recent tool use across local Senpai OpenHands root and recursively delegated conversations without exposing tool arguments. Use for provider comparisons, tool-loop diagnosis, status-poll analysis, error rates, and latency reports.

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。

This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Use this skill when the user provides chart images and requests technical analysis, trend identification, support/resistance levels, scenario planning, or probability assessments based purely on chart data without consideration of news or fundamental factors.

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。

Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.

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 professional reports from analysis results. Use when user needs to create formatted documents summarizing findings.

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。

Orchestrate complex development with AUTOMATIC parallel subagent execution, continuous dispatch scheduling, dependency analysis, file conflict detection, and IOSM quality gates. Analyzes task dependencies, builds critical path, launches parallel background workers with lock management, monitors progress, auto-spawns from discoveries. Use for multi-file features, parallel implementation streams, automated task decomposition, brownfield refactoring, or when user mentions "parallel agents", "orchestrate", "swarm", "continuous dispatch", "automatic scheduling", "PRD", "quality gates", "decompose work", "Mixed/brownfield".

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 debugging the Linux kernel: kgdb and kdb, ftrace and kprobes, dynamic debug, kdump and crash analysis, or printk levels on a live or crashed target.

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 writing an SELinux or AppArmor policy, a seccomp-bpf filter, enabling CET, PAC, or BTI, or triaging a kernel CVE. Not for KASAN report analysis: use kernel-debugging.

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 profiling with Intel VTune or AMD uProf for hotspots, top-down pipeline stalls, memory-bound analysis, or roofline data. Not for raw perf stat counters: use linux-perf.

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 static archives with ar, stripping or converting binaries, mapping crash addresses with addr2line, or demangling C++ symbols. Not for ELF analysis: use elf-inspection.

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 the user asks about recent engineering work, what the team is working on, planning or roadmap material, or an explicitly requested Slack summary. Not for remote or irreversible 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。

Use when a user needs to create or improve a deterministic, engine-agnostic fuzz harness for raw or structured target inputs. Not for coverage measurement: use fuzzing-coverage-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。

Use when a user needs to measure fuzz corpus coverage, explain a coverage plateau, or turn uncovered regions into campaign work. Not for harness creation: use fuzz-harness-writing.

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 code mixes units, fixed-point precisions, scaling factors, rates, prices, shares, or conversions. Not for type-level unit modeling: use type-driven.

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。