「eval」の検索結果

See the difference between Chat and Cowork with a live side-by-side comparison for understanding why Cowork is built differently. Use when evaluating AI tools, for comparing chat versus agent capabilities, during an AI tool decision, when switching from ChatGPT or Claude Chat, or when the user says "what is different about cowork", "cowork vs chat", "why not just use chatgpt", "show me the difference", "compare chat and cowork", or "why should I use cowork instead of chat".

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Gathers information from multiple sources in parallel, compares what they say, flags where they agree or conflict, and delivers a clean synthesis with a confidence rating for each finding. Useful for making evidence-backed decisions, when evaluating competing claims, during due diligence on a vendor or market, and for building research briefs before strategy sessions. Use when the user says "research this", "synthesize multiple sources", "compare sources", "research report", "what does the evidence say", "gather information on", or "deep dive into".

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URLScan.io API reference. URL submission, scanning, and result retrieval.

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Structured threat assessment methodology. Intent + Capability + Opportunity = Threat Level. Use when formally evaluating a threat. Prefers graded evidence items from /quality-of-information-check and runs that skill first when handed raw URLs or text. Confidence is capped by the weakest load-bearing claim, and at Moderate when the evidence is ungraded.

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Use when you need to classify an IP as internet scanner noise vs. targeted activity. Returns noise/riot flags, classification (benign/malicious/unknown), actor name if known. IP-only. Commonly invoked by /ip-investigation to filter out mass-scanning noise. Retrieval only.

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Use when you need host reconnaissance for an IP or domain — open ports, services, banners, OS detection, vulnerabilities. For domains, resolves DNS first then queries the IP. Commonly invoked by /ip-investigation and /domain-investigation. Retrieval only.

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Use when you need abuse-report history for an IPv4/IPv6 address — confidence score, total reports, distinct reporters, usage type. IP-only. Commonly invoked by /ip-investigation. Retrieval only.

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Use when you need deep host + certificate reconnaissance for an IP or need to run a Censys search query. Returns services, TLS certificates, ASN, and location. Free tier is severely limited (250 queries/month) — use sparingly. Retrieval only.

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Use when you need to check an IP, domain, file hash, or URL against AlienVault OTX community pulses. Returns pulse count, key pulses, tags, related indicators, and passive DNS. Commonly invoked by investigation skills to pull community context. Retrieval only — does not interpret.

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Analysis of Competing Hypotheses — structured technique for evaluating multiple explanations against evidence. Use when facing ambiguous attribution or multiple plausible scenarios. Prefers graded evidence items from /quality-of-information-check and runs that skill first when handed raw URLs or text. Runs on ungraded evidence when asked, labelled as such, unweighted, and capped at Moderate confidence.

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Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.

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Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.

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Design effective reasoning processes for AI agents and optimize decision-making strategies. Use when designing agent prompts, improving decision quality, implementing specialized reasoning modes, creating reasoning traces, or debugging agent mistakes. Covers prompting, chain-of-thought, reasoning depth, and decision evaluation.

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Expert prompt engineer specializing in designing, optimizing, and managing prompts for large language models. Masters prompt architecture, evaluation frameworks, and production prompt systems with focus on reliability, efficiency, and measurable outcomes.

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Assesses agent capabilities by analyzing agent files and determining what tasks they can handle. Use when you need to evaluate if an existing agent can handle a task or if a new agent is needed. Reviews agent descriptions, skills, and workflows to determine capability match.

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Audit cloud costs, optimize API token usage, and evaluate pricing models.

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Design and evaluate programmatic SEO strategies for creating SEO-driven pages at scale using templates and structured data.

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Intercepts and analyzes HTTP/HTTPS traffic from mobile applications using Burp Suite proxy to identify insecure API communications, authentication flaws, data leakage, and server-side vulnerabilities. Use when performing mobile application penetration testing, assessing API security, or evaluating client-server communication patterns. Activates for requests involving mobile traffic interception, Burp Suite mobile proxy, API security testing, or mobile HTTPS analysis.

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Use when pricing, packaging, plan structure, or monetization tradeoffs need to be evaluated against positioning, conversion, and margin.

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Evaluate pricing changes using ARPU, conversion, churn risk, NRR, and payback. Use when deciding whether a pricing move should ship.

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You are an expert in creating competitor comparison and alternative pages. Your goal is to build pages that rank for competitive search terms, provide genuine value to evaluators, and position your product effectively.

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Improve an existing skill or repository through isolated proposals, reproducible evaluation and evidence-based acceptance. Use for self-evolve or skill improvement.

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Analyze historical VS Code GitHub Copilot Chat sessions by model, reasoning effort, AIU, time, reliability, workflow behavior, and external quality evidence, or safely prune workspace-scoped local chat history by age. Use for session analysis, repeated-task retrospectives, model evaluation, cost/performance analysis, and old session cleanup.

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"Apply the Knowledge-Based View (Grant, 1996) and Nonaka and Takeuchi's SECI model to analyze how organizations create, transfer, and integrate knowledge for competitive advantage. Use this skill when the user needs to design knowledge management systems, understand why knowledge transfer fails across teams, evaluate knowledge creation processes, or when they ask 'how do we capture tacit knowledge', 'why does knowledge stay siloed', or 'how can we turn individual expertise into organizational capability'.".

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。