「feed」の検索結果

When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.

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。

Runs one or more installed review lenses — adversarial critique, edge cases, verification gaps, structure, prose — and reports triaged findings. Use when, and only when, the user asks you to review a diff, a pull request, or an artifact — code or documents, one or many — and actually says "review"; an explicit skill:bmad-review directive from another skill counts as that ask. A request to act on feedback from an earlier review is a change, not a review. Never invoke this uninvited, including on edits you just made.

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。

只在用户明确要求提交 GitHub Issue、GitHub Bug Report 或 GitHub Feature Request 时使用。用户只说“提交问题”“提交反馈”“上报 bug”“这是个 bug”或描述功能建议但未点名 GitHub 时不得触发，必须改用 cherry-studio-feedback 并默认提交飞书。

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 Cherry Studio 用户希望报告、提交或整理 BUG、UI/UX 问题或功能建议，但未明确要求创建 GitHub Issue。

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。

Operates Fictiv (app.fictiv.com), the on-demand manufacturing platform, end to end in the user's browser. Covers uploading CAD parts, configuring process, material, finish, threads, tolerances and inspections, getting instant or manual quotes, reading and fixing DFM feedback, choosing lead time and region, checking out and paying (card or PO), tracking orders, reordering, and troubleshooting. Applies when the user mentions Fictiv, wants a part CNC machined, 3D printed, sheet-metal fabricated, urethane cast, injection or compression molded, or die cast through an online service, asks to "get a quote" or "order parts" for a STEP/SLDPRT/STL file, wants to check a Fictiv quote or order status, or has a problem with a Fictiv upload, DFM warning, price or checkout. Also applies when the user wants custom parts manufactured and has a Fictiv account, even if Fictiv is not named.

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。

Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.

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。

Crypto market leaderboards — ranked aggregate feeds across the whole market: social-hype/sentiment rank, trending / top-search / Binance Alpha / tokenized-stocks rank, smart-money net-inflow rank (which tokens received the most inflow), top meme tokens by breakout score on Pulse launchpad, top trader PnL leaderboard (ALL / KOL). Use whenever the user wants a ranked list of tokens or addresses by some metric — phrases like "trending tokens", "top N by hype", "leaderboard", "rank by X", "biggest inflows", "top traders this week".

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。

Turns resume duties into truthful impact bullets. Questions the user role by role to dig out achievements, asks for real numbers or honest ranges (never invents them), and writes concise bullets in XYZ, CAR, scope or qualitative form. Use when the user says "rewrite my bullets", "make this bullet stronger", "quantify my resume", "turn my duties into achievements", "improve my experience section", "my resume sounds boring", "I don't have any numbers", pastes resume lines for feedback, or works in a low-number job (nursing, teaching, care, trades, admin, creative). With the Reactive Resume MCP server connected, it edits experience, project, volunteer and education descriptions with apply_resume_patch after the user approves. Use resume-content-guide instead for which sections or details belong and for summaries or headlines, resume-tailor to fit one job posting, interview-prep or mock-interview for interview stories and practice, and resume-builder to build a resume from scratch.

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 and implement microinteractions, motion design, transitions, and user feedback patterns. Use when adding polish to UI interactions, implementing loading states, or creating delightful user experiences.

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。

Align a fine-tuned model with preference data using DPO, ORPO, KTO, or SimPO. Use when preference pairs or thumbs-up/down feedback exist, when choosing between preference-optimization methods, or when a DPO run needs hyperparameters or debugging.

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。

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

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。

Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.

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。

Infuse learning strategies and metacognition into a concept-centered OpenMAIC classroom as a parallel goal. Use when the user wants students to learn how to learn while studying a subject: retrieval practice, self-explanation, prediction before feedback, monitoring understanding, deliberate review, or productive failure. Do not use when learning science or study skills should be the standalone subject of the lesson.

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。

Spin up a personal, motivating daily focus board that renders in a browser canvas and that the user drives by talking to their AI partner. Tasks track status (to-do → in progress → done) with timestamped progress notes and roll up into a "today's momentum" feed; numeric-goal tasks (pages, pomodoros, reps) render as progress-bar counters. Executive-function / neurodivergent-friendly by design: Focus mode, kind "not today" carryover (no overdue-shaming), a brain-dump box, reduced-motion, and gentle deadline countdowns. Add, reorder, and relabel tasks live, assign Eisenhower priority (Do first / Schedule / Delegate / Later), open with an above/below-the-line check-in and a daily mantra, and save an end-of-day recap. Use when someone wants to plan their day, stay focused, kick off a work session, or track progress. Progress persists in the browser (localStorage).

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。

Copilot left 14 review comments on your PR — half are nits. Hours of fix → reply → resolve → re-request, and each round lands MORE comments. This skill runs loop engineering: auto-triggers Copilot Code Review via GraphQL (no @copilot mention), triages every open thread (Copilot, humans, advanced-security) with a fix / decline / escalate rubric, dispatches parallel fix sub-agents that obey the repo build/test/lint conventions, commits per iteration, replies+resolves citing the pushed SHA, then re-triggers until HEAD is reviewed with zero threads awaiting the agent's reply (remaining open threads are explicit hand-offs to the human — escalated declines, design tradeoffs). You merge a clean PR; the bot runs it. Trigger phrases: "address copilot comments", "run a copilot review loop", "fix this PR", "iterate on copilot feedback". Repo-agnostic, gh CLI + PowerShell. Full autopilot needs repo Triage/Write; external PR authors get single-iteration mode plus manual re-trigger (UI 🔄 or substantive-commit push).

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 and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, update_annotations, labeling queue, annotate record, or human review.

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。

Parse an investor or client onboarding packet into structured KYC fields — identity, ownership, control, source of funds, and document inventory. Use as the first step of KYC screening; output feeds the rules engine.

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。

Deploy and configure Zeek (formerly Bro) to passively analyze network traffic, generate structured connection/DNS/HTTP/SSL/file logs, detect anomalous behavior, and write custom scripts for organization-specific threats. Use for passive monitoring at network choke points, feeding SIEM/threat hunting with protocol metadata, or retrospective log analysis during incident response; not a substitute for inline IDS/IPS or host agents.

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。

Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

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。

Evaluates and selects Threat Intelligence Platform (TIP) products based on organizational requirements including feed integration capability, STIX/TAXII support, workflow automation, analyst interface, and total cost of ownership. Use when conducting a TIP procurement, migrating between TIP solutions, or assessing whether the current TIP meets program maturity requirements. Activates for requests involving ThreatConnect, MISP, OpenCTI, Anomali, EclecticIQ, or TIP procurement decisions.

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。

Configures Windows Event Logging with advanced audit policies to generate high-fidelity security events for threat detection and forensic investigation. Use when enabling audit policies for logon events, process creation, privilege use, and object access to feed SIEM detection rules. Activates for requests involving Windows audit policy, event log configuration, security logging, or detection-oriented logging.

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。

Implement a phishing report button (Microsoft 365 built-in Report button or third-party like KnowBe4/Cofense) in email clients with a SOAR-driven automated triage workflow that classifies reported emails, extracts IOCs, takes remediation actions, and gives feedback to reporters. Use when deploying user-reported phishing intake or automating triage of the resulting reporting mailbox.

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 and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment workflows, STIX/TAXII interoperability, and analyst dashboards. Use when architecting or standing up a centralized CTI platform to collect, analyze, and disseminate threat intelligence across a security team.

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。

Deploy MISP, configure threat feeds (MISP community, freetext, TAXII, CSV), and use the PyMISP API to programmatically fetch, add, and search events and IOCs, building automated collection pipelines that aggregate indicators from community and commercial sources. Use when gathering, storing, or correlating IOCs and threat intelligence, or when scripting MISP ingestion via PyMISP.

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。