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概要と使いどころ
Systematic exploratory data analysis. Activate when a dataset needs profiling — structure check, nulls, outliers, distributions, correlations — before deeper analysis begins.
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 peer review for analytical work. Use when reviewing teammates' analysis, providing constructive feedback, or establishing analysis quality standards.
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。
Rigorous A/B test statistical analysis. Use when analyzing experiment results, calculating statistical significance, checking for sample ratio mismatch, or validating test design before launch.
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 concise executive summaries from detailed analysis. Use when preparing board decks, executive briefings, or condensing complex analysis into decision-ready formats for senior audiences.
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。
Performs deep AI-powered analysis and understanding of long-form videos (up to 3 hours, 10GB) using Volcengine LAS large language models. Video analysis, video comprehension, and video summarization — generates comprehensive video summaries, video recaps, chapter breakdowns, event timelines, key moments, and structured content indexing. Supports behavior detection, action detection, video annotation, video tagging, and video content recognition. Enables intelligent video question answering — ask questions about video content and get AI answers. Handles long meeting recordings, lecture videos, webinars, surveillance and security footage, movies, tutorials, and any long video that needs detailed understanding. Async processing with submit-poll workflow. Use this skill when the user wants to analyze or understand long videos (up to 3h/10GB) with LLM-based deep comprehension, summarize video content or generate recaps, extract chapters/key moments/timelines from videos, do video Q&A (ask questions about video content), detect actions/behaviors in videos, review meeting recordings/lectures/webinars, or get structured video descriptions.
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 you need to verify Java performance optimizations by comparing profiling results before and after refactoring — including baseline validation, post-refactoring report generation, quantitative before/after metrics comparison, side-by-side flamegraph analysis, regression detection, or creating profiling-comparison-analysis and profiling-final-results documentation. This should trigger for requests such as Verify performance fix; Verify the performance; Verify the memory; Verify the threading; Compare before and after profiling results; Check for performance regressions after refactoring. Part of Plinth Toolkit
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 problem or issue needs explicit framing before deeper analysis begins — establishing the Problem statement, Current state, Desired state, Stakeholders, and Success criteria. This should trigger when an issue's Problem Framing point of view needs evaluation, or when a maintainer directly asks to frame a problem before root-cause analysis, design, or planning begins. Part of Plinth Toolkit
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 framed and root-caused problem needs its assumptions made explicit before design or planning begins — explicit Assumptions, Unknowns, and a Validation plan. This should trigger when an issue's Assumption Analysis point of view needs evaluation, or when a maintainer directly asks to surface hidden assumptions and unknowns before committing to an approach. Part of Plinth Toolkit
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 framed problem needs root-cause investigation rather than a symptom-level fix, applying Five Whys, Fishbone (Ishikawa), Current Reality Tree, and constraint identification. This should trigger when an issue's Root Cause Analysis point of view needs evaluation, or when a maintainer directly asks to find the root cause of a problem before proposing a fix. Part of Plinth Toolkit
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。
Assessment: read-only inspection, codebase overview, value analysis, health checks, ADR consultation, decision analysis, multi-perspective critique.
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。
SEO analysis and optimization specialist. Use when conducting technical SEO audits, optimizing meta tags, analyzing Core Web Vitals, or improving search engine rankings. Focuses on actionable 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。
Comprehensive debugging specialist for errors, test failures, log analysis, and system problems. Use when encountering issues, analyzing error logs, investigating system anomalies, debugging production issues, analyzing stack traces, or identifying root causes. Combines general debugging workflows with error pattern detection and log 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。
Meta-cognitive reasoning specialist for evidence-based analysis, hypothesis testing, and cognitive failure prevention. Use when conducting reviews, making assessments, debugging complex issues, or any task requiring rigorous analytical reasoning. Prevents premature conclusions, assumption-based errors, and pattern matching without verification.
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 analyzing binary structure, disassembling code, or decompiling functions. Deep static analysis via radare2 (r2) and Ghidra headless - function enumeration, cross-references (xrefs), decompilation, control flow graphs. Keywords - "disassemble", "decompile", "what does this function do", "find functions", "analyze code", "r2", "ghidra", "pdg", "afl"
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 you need to run a binary, trace execution, or observe runtime behavior. Runtime analysis via QEMU emulation, GDB debugging, and Frida hooking - syscall tracing (strace), breakpoints, memory inspection, function interception. Keywords - "run binary", "execute", "debug", "trace syscalls", "set breakpoint", "qemu", "gdb", "frida", "strace", "watch memory"
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 binaries, executables, or bytecode to understand what they do or how they work. Triggers on "binary", "executable", "ELF", "what does this do", "reverse engineer", "disassemble", "decompile", "pyc file", "python bytecode", "analyze binary", "figure out", "marshal". Routes to sub-skills for triage, static analysis, dynamic analysis, synthesis, or tool 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。
Review a Chinese mathematical-modeling problem-analysis section against the original problem, checking task classification, data reasoning, cross-problem linkage, model-choice rationale, validation planning, chapter boundaries, and the overall solution framework. Use for diagnosis, not automatic full rewriting.
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 your security posture against the NIST Cybersecurity Framework 2.0 (Govern, Identify, Protect, Detect, Respond, Recover). Produce a gap analysis, current/target tier assessment, and roadmap in the governance language that boards, auditors, and CISOs actually use. Use when the user mentions 'NIST CSF,' 'CSF 2.0,' 'cybersecurity framework,' 'security posture,' 'governance mapping,' 'CSF gap analysis,' 'CSF tiers,' 'cybersecurity maturity,' 'security roadmap,' 'CISO report,' 'board reporting,' 'security program,' or needs to translate technical findings into governance language.
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 a specific CVE or vulnerability disclosure end-to-end — what version is affected, is your code reachable, is there a public PoC, is there a patch, what's the exposure window, what's the mitigation if you can't patch immediately. Use when the user mentions 'CVE,' 'vulnerability research,' 'is this CVE relevant,' 'zero-day,' 'CISA KEV,' 'GitHub Security Advisory,' 'reachability analysis,' 'patch analysis,' 'exploit availability,' 'EPSS,' 'CVSS,' or 'should we drop everything and patch this.'
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。
Token holder distribution, concentration metrics, insider detection, and supply analysis for Solana tokens
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。
DeFi yield evaluation including fee APR, real vs nominal yield, net APY after costs, and yield sustainability 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。
DEX liquidity depth assessment, slippage estimation, and pool composition analysis for Solana tokens
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。
Cross-asset correlation analysis including rolling correlation, hierarchical clustering, tail dependence, and regime-dependent correlation
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。
Cointegration testing for pairs trading using Engle-Granger, Johansen, and rolling stability 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。