808 件 ・ 関連度順
概要と使いどころ
Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
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, update 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。
Apply systematic performance optimization techniques when writing or reviewing code. Use when optimizing hot paths, reducing latency, improving throughput, fixing performance regressions, or when the user mentions performance, optimization, speed, latency, throughput, profiling, or benchmarking.
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。
Scan global talent markets via GitHub/Arxiv/LinkedIn APIs, build talent heatmaps with salary benchmarks, identify Tier S/A/B/C candidates. Use when: quarterly talent scanning, critical role hiring, competitive intelligence on talent pools. Includes real API integrations and data pipeline.
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。
Design irresistible offer packages with real salary benchmarks, negotiation playbooks, and competitive counter-strategies. Co-designed with Siku (司库). Includes total compensation calculator, negotiation scripts, and BATNA 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。
Test and assure quality — test plan, QA, coverage, unit test, integration test, end-to-end, performance, benchmark, regression. Applies TDD and FIRST principles for the CTO office's tester.
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。
Set up eval-based QA for Python LLM applications: instrument the app, build golden datasets, write and run eval tests, and iterate on failures. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.
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。
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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。
Inspect, benchmark, and monitor Web3 RPC endpoints — latency checks, method support, chain detection, and health scoring.
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。
Gates CI on perf regressions. Automated threshold alerts, baseline tracking, trend 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。
Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP 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。
Analyzes and optimizes SQL queries using EXPLAIN plans, index recommendations, query rewrites, and performance benchmarking. Use for "query optimization", "slow queries", "database performance", or "EXPLAIN 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。
Creates load and performance tests with k6, Artillery, or autocannon to validate system behavior under stress. Use when users request "load testing", "performance testing", "stress testing", "k6 setup", or "benchmark 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。
Builds repeatable evaluation systems with golden datasets, scoring rubrics, pass/fail thresholds, and regression reports. Use for "LLM evaluation", "testing AI systems", "quality assurance", or "model benchmarking".
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。
Analyzes email sequence performance metrics. Evaluates open rates, click rates, reply rates, and conversion by step. Identifies drop-off points, benchmarks against industry averages, and recommends optimizations.
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。