'dog' 검색 결과

브라우저에서 웹 앱을 직접 조작해 폼, 화면 이동, 레이아웃 문제와 JavaScript 오류를 확인합니다. 재현 절차와 스크린샷을 담아 심각도와 유형별로 보고서를 작성합니다.

• 출시 전 주요 사용자 흐름 점검
• 폼에 정상값, 잘못된 값, 빈 값 입력
• 레이아웃 문제와 JavaScript 오류 기록

Build real-time detection for ransomware encryption by combining changes in data randomness with file modification rates, renames, and process activity. Define behavioral scores and response thresholds, then check detection accuracy and monitoring overhead.

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• Building ransomware monitoring for endpoints and file servers
• Tuning detection thresholds to reduce false positives
• Investigating processes suspected of encrypting files

Test user journeys affected by a branch’s changes in a real browser. Check correctness and the experience for intended users, fix small defects with regression tests, and commit fixes alongside a report documenting results and unresolved decisions.

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• Check user-facing changes before a PR is merged
• Test complete user journeys affected by a branch
• Fix small defects and add regression tests

Monitor other agent teams for abandoned work, process drift, off-task activity, and excessive token use. It guides evidence checks after alerts and chooses a proportionate response, from notifying the team’s coordinator to escalating to a human.

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• Check whether unfinished work was abandoned
• Detect process drift or off-task activity
• Investigate excessive token use

Explore a web application as a user to find bugs and usability problems. Produce a structured report with reproducible steps, screenshots, and videos for interaction issues, giving responsible teams clear evidence to investigate.

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• Checking core workflows before release
• Finding usability problems in forms and navigation
• Preparing bug reports with reproduction evidence

Implement HTTP headers that pass GitHub Actions secrets through environment variables in gh-aw’s copilot engine. This reference explains secret extraction, generated MCP configuration, execution-step settings, and tests for keeping secret values out of configuration files.

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• Passing API keys to HTTP MCP servers
• Reviewing generated configuration for secret handling
• Supporting secret expressions with default values

Plan and implement instrumental variable estimation and propensity score matching, methods for estimating causal effects under different assumptions. Includes Python, R, and Stata examples, diagnostic checks, and guidance on interpreting and reporting results.

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• Choose between instrumental variables and matching
• Implement two-stage least squares estimation
• Check weak instruments and estimation diagnostics

Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes. Always search tools first for current schemas.

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Lomb-Scargle periodogram for finding periodic signals in unevenly sampled time series data. Use when analyzing light curves, radial velocity data, or any astronomical time series to detect periodic variations. Works for stellar rotation, pulsation, eclipsing binaries, and general periodic phenomena. Based on lightkurve library.

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Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", or "test this app" on mobile. Produces a structured report with reproducible evidence: screenshots, optional repro videos, and detailed steps for every issue.

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Diagnoses macOS system-level slowness, heat and fleet-wide timeouts: high load average, leaked per-session child processes (MCP servers, helpers), fork storms, busy loops. Use when the Mac feels slow or hot, fans spin up, or everything times out at once (电脑发烫/卡顿/负载高/全部超时). Not for single-app bugs, network slowness (use tunnel-doctor), launchd watchdog design (use macos-watchdog), or disk-full (use macos-cleaner).

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Designs and audits macOS launchd watchdogs: LaunchAgent/LaunchDaemon setup, plist edits, scheduled self-healing, repeated notifications, apps reopening after quit, crash/repair loops, Script Editor alerts, stop/disable/restart, cooldown/backoff, notification throttling, alert decisions, schedule readback, WatchPaths/FSEvents event triggers. Supports periodic observers. launchd 守护进程、常驻任务、开机自启、后台监控、定时自愈、通知来源排查、事件驱动监控。

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Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.

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Implement Datadog monitoring and APM for infrastructure and applications. Configure agents, create dashboards, set up alerts, and implement distributed tracing. Use when implementing enterprise monitoring, APM, or unified observability platforms.

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Lightweight 3D effects for decorative elements and micro-interactions using Zdog, Vanta.js, and Vanilla-Tilt.js. Use this skill when adding pseudo-3D illustrations, animated backgrounds, parallax tilt effects, decorative 3D elements, or subtle depth effects without heavy frameworks. Triggers on tasks involving Zdog pseudo-3D, Vanta.js backgrounds, Vanilla-Tilt parallax, card tilt effects, hero section animations, or lightweight landing page visuals. Ideal for performance-focused designs.

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Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.

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Removes the egregore watchdog daemon and its associated files. Use when stopping automated session relaunching or cleaning up egregore infrastructure.

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Installs egregore watchdog daemon via launchd or systemd for autonomous relaunching. Use when setting up egregore on a new machine. Do not use on CI/CD runners.

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Inspect an unfamiliar repository, interpret a broad Markdown user journey at runtime, operate the real product through its supported web, API, CLI, desktop, or mobile surface, and produce an auditable pass, fail, or blocked judgment with screenshots, logs, recordings, and a step timeline when available. Use when asked to run smoke tests, validate an end-to-end user journey, dogfood a product, test a release candidate, or execute a non-deterministic workflow that may include authentication or human checkpoints. Do not use as a substitute for deterministic unit, integration, or scenario tests.

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Analyze a software repository at the latest remote main commit and turn its implemented architecture into a citation-backed interactive isometric system map with a legend, selectable infrastructure buildings, dependency and payload flows, and plain-language learner explanations. For eligible public GitHub repositories, also contribute the verified map to tamdogood/CodeTerrain with a pull request. Use when a user provides a repository URL or asks to visualize, explore, learn, explain, or map a repo's architecture, infrastructure, runtime control flow, data flow, services, queues, stores, external systems, or deployment topology in an interactive UI.

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Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.

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[BETA] Hands-off end-to-end branch dogfood pass with browser testing, auto-fixes, regression tests, and fix commits.

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Dogfooding discovery agent — establish human-approved project baseline from public docs without code inspection

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Cyclical dogfooding loop: test AI-AGENT-STORIES.md against the live graph, discover new stories, analyze gaps, fix root causes, re-test, write report. Use when: (1) user says "/gap-loop", (2) periodic dogfooding session, (3) after a release or major feature to re-validate stories, (4) before sprint planning to prioritize product gaps.

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