「recommend」の検索結果

Checks hardcoded secrets, SQL injection, XSS, insecure dependencies, missing input validation. Returns findings with severity, location, effort, recommendations.

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 application logs: classifies errors, checks log quality/format, maps stack traces to source, recommends fixes.

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。

Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.

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 to measure command execution time or optimize a feedback loop. Records explicit measurements and recommends faster alternatives such as unit tests versus integration tests. It is opt-in; it does not run on every command.

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。

Identify customers most likely to churn before they leave. Uses behavioral signals, usage patterns, and engagement data to score accounts and recommend retention 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。

You are an AI Automation Agency strategist. Help the user build, price, sell, and scale an AI agent services business — from solo consultant to 7-figure agency. Every recommendation must be specifi...

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。

Structured multi-criteria decision analysis for ranking options with weights, constraints, confidence, tradeoff reasoning, sensitivity analysis, and explainable recommendations. Use when the user asks for decision support, MCDA, weighted scoring, prioritization, vendor selection, route planning, hiring shortlist ranking, tool comparison, procurement decisions, or auditable agent decision logic.

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。

Adaptive testing engine with IRT/CAT, AI question generation, and personalized learning recommendations

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。

Save any product to a universal wishlist. Converts any product URL into a one-click "save for later" link. Works with any retailer, any AI platform, zero setup.

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 non-binding follow-up action suggestions from lead summaries or lead lists. Use when users ask for next best actions, call list for hot leads, or follow-up draft plan without automatic execution. Recommended chain: summary-generator then action-suggester then supervisor approval. Do not use for parsing, storage, or autonomous action execution.

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。

Two superpowers for AI agents: a collective brain and a Base ecosystem mentor. BRAIN: Before debugging/compiling/architecting, search for existing solutions. After solving, propose so no agent repeats your mistake. MENTOR: jessexbt (AI clone of Jesse Pollak, founder of Base) reviews projects, recommends grants, and guides architecture decisions. Consult him directly when building on Base/crypto/onchain/web3. Activate on: errors, bugs, compilation failures, architecture decisions, patterns, project reviews, Base, crypto, web3, 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。

Build signal-based forms in Angular v21+ using the new Signal Forms API. Use for form creation with automatic two-way binding, schema-based validation, field state management, and dynamic forms. Triggers on form implementation, adding validation, creating multi-step forms, or building forms with conditional fields. Signal Forms are experimental but recommended for new Angular projects. Don't use for template-driven forms without signals or third-party form libraries like Formly or ngx-formly.

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。

Safely auto-detect the current machine's hardware (GPU, VRAM, system RAM, OS) with read-only commands, then recommend the top 3 local AI models to run — most powerful that fits, best for coding, and best small-and-fast — each with download links. Use when someone asks "what AI models can my computer run" or "what's the best local model for my rig".

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。

One-shot GEO visibility check for a brand using Xpoz. Runs the buyer questions that matter through Claude, ChatGPT, and Gemini, and reports where the brand appears, who wins instead, and which surfaces the answers are assembled from. Use when asked to "check my AI visibility", "does ChatGPT recommend us", "GEO audit", "where do we show up in AI answers", or "who wins our category in AI answers".

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。

Ask Claude, ChatGPT, and Gemini a question and capture the full trace behind the answer (the search queries each engine ran, the pages it retrieved, and the sources it cited, span by span). Use when asked to "trace an AI answer", "see what AI engines cite", "check AI citations", "which sources does ChatGPT/Claude/Gemini use", "why does the AI recommend X", or for any GEO (Generative Engine Optimization) measurement.

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 an incoming workflow upgrade — a skill, MCP server, subagent, library, external service, prompt, or pattern — through one disciplined pipeline before adopting it. Security is a blocking gate. Records every verdict so the same thing is never evaluated twice. Use when considering a new tool from a post, repo, or recommendation. Triggers — "vet this", "should we adopt", "is this safe to install", "evaluate this skill/MCP", "what do you think of this tool".

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 team of 50 LLM personas through a 30-round structured debate to predict market direction. Uses the Canvas Agent Swarm Service — the same shared infrastructure other skills use for smaller agent teams. Output is an influence-weighted consensus direction + trade recommendation with a transparent record of every argument, research query, and cross-examination.

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。

Produces internal case viability and conflict check memos for personal injury litigation intake. Screens conflicts, assesses liability and damages, checks statute of limitations, and outputs an accept/decline recommendation. Use when evaluating new PI intake, running conflict checks, assessing case merit pre-filing, or preparing acceptance memos.

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。

Produces U.S. litigation case chronologies with dated timelines, executive summaries, source attribution, gap analysis, and investigation recommendations. Use when asked for a chronology, timeline, case summary, or executive summary of a legal matter, or during case intake, deposition prep, or trial prep.

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。

Produces a Rule 506(d) bad actor disqualification review for private securities offerings, including a covered persons register, tailored questionnaires mapping to each disqualifying event category, a documented reasonable-care diligence record, and classification analysis of flagged events with remediation or disclosure recommendations. Use this skill when conducting Rule 506(d) diligence, identifying covered persons for a Regulation D offering, drafting bad actor questionnaires, or analyzing potential disqualifying events involving criminal convictions, SEC orders, SRO sanctions, or state regulatory actions. Also trigger when the user mentions bad actor screening, covered persons analysis, Rule 506(d) questionnaire, disqualification waiver, or reasonable care defense. Even if the user just says "bad actor check" or "506(d) diligence," use this 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。

AI compliance analysis for EU AI Act, ISO 42001, NIST AI RMF, GDPR, OECD, financial services regulations (SEC, FCA, FINRA, DORA, MiFID II), and other frameworks. Use when asked to generate a compliance checklist for an AI tool or use case, determine if a risk assessment is required, score an AI tool's risk level, identify where an AI tool or use case could run afoul of regulatory requirements, perform a gap analysis, recommend remediation steps, assess a vendor, draft an acceptable use policy, map training requirements, or review jurisdiction-specific AI rules. Triggers on phrases like "compliance checklist", "risk assessment", "risk score", "does this comply", "EU AI Act", "ISO 42001", "NIST AI RMF", "AI governance", "gap analysis", "vendor assessment", "acceptable use policy", "MNPI", "AI training requirements", or any request to evaluate an AI tool or use case for regulatory compliance or risk.

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。

Workflow navigator: scans project state (plans, reviews, tests, git) and recommends the next pipeline step. Use for 'what next?' or 'where am I?'. NOT for complexity routing (mk:scale-routing).

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。

Routing skill — recommends the correct mk:jira-* leaf for any Jira task. Triggers: 'jira', 'jira ticket', ambiguous Jira intent. NOT an executor — every actual operation forks via a leaf 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。

Turn a raw idea into ONE honest recommendation: interview one question at a time until confirmed, then give a verdict with trade-offs and a checklist. Not for options or debate.

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。