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cccskills

'testing' 검색 결과

4.2천건 · 관련도순

gstack

무료

Fast headless browser for QA testing and site dogfooding. Navigate pages, interact with elements, verify state, diff before/after, take annotated screenshots, test responsive layouts, forms, uploads, dialogs, and capture bug evidence. Use when asked to open or test a site, verify a deployment, dogfood a user flow, or file a bug with screenshots. (gstack)

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

mostafasudo/appilot32026년 9월 14일 업데이트

browse

무료

Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence. Use when asked to "open in browser", "test the site", "take a screenshot", or "dogfood this". (gstack)

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

mostafasudo/appilot32026년 9월 14일 업데이트

Microsoft Pragmatic Rust Guidelines for implementing, reviewing, and documenting idiomatic Rust. Use when working on Rust APIs, error handling, unsafe code, concurrency, async code, performance, testing, documentation, or agent-facing design.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

heyAyushh/stacc32026년 9월 21일 업데이트

Expert TypeScript engineering with advanced patterns, architectural design, performance optimization, testing strategies, and production-grade code quality. Use when building scalable TypeScript applications, implementing complex type systems, optimizing performance, designing maintainable architectures, or when the user asks for TypeScript engineering excellence, advanced patterns, or professional-grade code practices.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

heyAyushh/stacc32026년 9월 21일 업데이트

End-to-end Solana development playbook (Jan 2026). Prefer Solana Foundation framework-kit (@solana/client + @solana/react-hooks) for React/Next.js UI. Prefer @solana/kit for all new client/RPC/transaction code. When legacy dependencies require web3.js, isolate it behind @solana/web3-compat (or @solana/web3.js as a true legacy fallback). Covers wallet-standard-first connection (incl. ConnectorKit), Anchor/Pinocchio programs, Codama-based client generation, LiteSVM/Mollusk/Surfpool testing, and security checklists.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

heyAyushh/stacc32026년 9월 21일 업데이트

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

heyAyushh/stacc32026년 9월 21일 업데이트

Measure, profile, and fix performance bottlenecks — Core Web Vitals, backend latency, bundle size, and database queries. Load when performance requirements exist, users report slowness, profiling reveals bottlenecks, or the user asks to optimize load time, LCP, INP, CLS, or response time. Not for premature optimization without evidence. Pairs with browser-testing-with-devtools and ci-cd-and-automation for regression guards.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dvy1987/agent-loom32026년 8월 8일 업데이트

Design automated evaluation pipelines for LLM and agent systems — combining deterministic checks, statistical metrics, and LLM-as-judge scoring into repeatable, CI-integrated eval suites. Load when the user asks to set up automated evals, design an eval pipeline, integrate evals into CI/CD, create an eval suite, do eval-driven development, or says "automate my evals", "CI eval integration", "evaluation pipeline", "continuous evaluation", "monitoring eval quality", "set up regression testing for my agent". Sub-skill of eval-output orchestrator.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dvy1987/agent-loom32026년 8월 8일 업데이트

Surface every assumption embedded in a plan, strategy, or document, assess how critical and how validated each one is, and identify which ones to test first. Load when the user asks to map assumptions, surface hidden beliefs, find what must be true for this to work, run an assumption audit, or when deep-thinking diagnoses an assumption frame. Also triggers on "what are we assuming", "what must be true for this to work", or "find the untested beliefs". Based on David Bland and Alex Osterwalder's assumption mapping method from Testing Business Ideas.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dvy1987/agent-loom32026년 8월 8일 업데이트

Turn assumptions, funnel opportunities, and product questions into a prioritised, feasibility-checked experiment backlog. Filters by traffic reality, metric latency, and method feasibility — not just ICE/RICE scoring. Maintains a living portfolio with status (idea → designed → running → readout → archived). Load when the user says "what should we test next", "build an experiment backlog", "prioritise our tests", "where should we experiment", "what's worth testing", or when the experimentation orchestrator routes here.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dvy1987/agent-loom32026년 8월 8일 업데이트

Apply validated research paper insights to the current project codebase — improving architecture, code patterns, testing strategies, documentation, or workflows based on empirical findings. Load when learn-from-paper routes insights to the current project, or when the user asks to apply paper findings to this project, improve this codebase with research, use this paper to improve my project, or apply research to my code. Also triggers on "apply this to my project", "how can this paper help my codebase", "use these findings here", "implement paper recommendations", "use research to improve my code". Always called AFTER learn-from-paper has completed credibility and security checks — never ingests papers directly.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dvy1987/agent-loom32026년 8월 8일 업데이트

dogfood

무료

Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

q2805187159/Anvil32026년 6월 24일 업데이트

X-ray any AI model's behavioral patterns — refusal boundaries, hallucination tendencies, reasoning style, formatting defaults. No API key needed.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

Bash scripting workflow for creating production-ready shell scripts with defensive patterns, error handling, and testing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

Azure Resource Manager SDK for Microsoft Playwright Testing in .NET.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

Run Playwright tests at scale with cloud-hosted browsers and integrated Azure portal reporting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

Automated end-to-end UI testing and verification on an Android Emulator using ADB.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and domain dominance for red team operations and penetration testing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

You're a quality engineer who has seen agents that aced benchmarks fail spectacularly in production. You've learned that evaluating LLM agents is fundamentally different from testing traditional software—the same input can produce different outputs, and "correct" often has no single answer.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nimoqup046-collab/agora32026년 3월 26일 업데이트

Analyze spatial cell-cell interactions, neighborhoods, and niches in IMC/MIBI data with squidpy and imcRtools, covering neighborhood-enrichment permutation nulls, the abundance-vs-density confound, inhomogeneous Ripley's K, cellular-neighborhood discovery, graph-construction (contact vs proximity), and edge effects. Use when testing whether cell types co-locate, choosing a spatial null, building a neighbor graph, discovering tissue niches, or deciding whether a spatial pattern is real or a density/segmentation artifact.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

peacezha/HPClaw32026년 10월 11일 업데이트

Performs set operations on genomic intervals - intersect (-wa/-wb/-wo/-wao/-loj/-c/-v/-u), subtract (-A), merge (-d, -c/-o), complement, cluster, multiinter, unionbedg, map, and groupby - with bedtools (CLI) and pybedtools/pyranges/bioframe (Python). Covers the sorted-input contract and the -sorted chromosome-order footgun, reciprocal/fractional overlap (-f/-F/-r/-e) and the A-vs-B asymmetry, -split for spliced/BED12/BAM features, and jaccard/fisher as mechanics only. Use when finding overlapping or unique regions between BED/peak/feature files, building consensus peaksets, removing blacklisted regions, transferring annotation values onto intervals, or computing interval-set similarity; route overlap-significance testing to overlap-significance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

peacezha/HPClaw32026년 10월 11일 업데이트

Tests whether two genomic interval sets overlap (colocalize) more than expected by chance using a permutation test against a structured-genome null model. Covers bedtools fisher (analytic 2x2 screen), bedtools shuffle + jaccard permutation, GAT (isochore/GC-conditioned simulation with FDR), regioneR (flexible permutation, randomizeRegions vs circularRandomizeRegions, localZScore), LOLA (universe-relative Fisher against a region database), and GREAT/rGREAT (regulatory-domain binomial + hypergeometric for ontology-from-regions). Stresses the universe/background choice, matched background, blacklist exclusion, and multiple-testing control. Use when asking whether peaks/regions are enriched at enhancers/TFBS/features, scoring region-set colocalization or region-set enrichment, comparing CNV/SV concordance, or turning an overlap count into a defensible p-value.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

peacezha/HPClaw32026년 10월 11일 업데이트