「event」の検索結果

Cross-platform hooks reference for AI coding assistants — Claude Code, OpenAI Codex, GitHub Copilot, Cursor, Windsurf, and Amp. Covers hook authoring in Node.js (ESM and CJS) and Python, per-platform event schemas, inline-agent hooks and MCP in agent frontmatter, common JSON I/O, exit codes, best practices, and a fetch script to refresh docs from official sources. Use when writing, reviewing, or debugging hooks for any AI assistant.

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Guide for creating Claude Code plugin hooks — language selection heuristic (Node.js default, match project runtime when obvious), hooks.json configuration, event selection, prompt-based vs command hooks, ${CLAUDE_PLUGIN_ROOT} paths, stdio suppression, timeout sizing, and testing. Use when adding hooks to a plugin, creating PreToolUse/PostToolUse/Stop/SubagentStop/SessionStart/UserPromptSubmit hooks, or wiring hook scripts to hooks.json.

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Orchestrator context window discipline enforcement. Prevents the orchestrator from reading source files it will not edit, running diagnostic commands that waste context, and rationalizing delegation bypasses. Use when setting up orchestrator guardrails, reviewing delegation discipline, or diagnosing context window waste in multi-agent workflows. Activates PreToolUse hooks that surface decision points before source file reads and diagnostic command execution.

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Rigorous self-assessment checklist before marking any task as complete. Use when about to claim task completion, before final commit, when user asks "is it done?", or when transitioning from implementation to reporting. Prevents premature completion claims by requiring evidence for every assertion.

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Enforce anti-AI UI design rules based on the Uncodixfy methodology. Use when generating HTML, CSS, React, Vue, Svelte, or any frontend UI code. Prevents generic AI aesthetic — soft gradients, glassmorphism, hero sections in dashboards, oversized rounded corners, and decorative copy. Applies constraints from Linear/Raycast/Stripe/GitHub design philosophy for functional, honest, human-designed interfaces. Triggers on UI generation, dashboard building, component creation, CSS styling, landing page design, or any task producing visual interface code.

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DRAFT. Score Luma/RSVP lists, approve against capacity, produce host-hit shortlists and day-of door packs. Systems framing — not a marketing CSV dump. Not installed by deepline skills.

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ACCESS-GATED beta. Deepline Monitors are provider event feeds (job posts, email replies, funding, intent) that stream into your warehouse and trigger plays. Only use if you have monitor access: run `deepline monitors status` first; if it reports no access, do NOT use this recipe — tell the user to contact the Deepline team.

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Storyboard a papercut script before any code. Writes the Camera / Cut table, one block per scene with frame-level events on each stressed word, the SFX plan and the proof beat. Use for "storyboard this script" or "plan the camera moves and cuts".

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Deploys websites, web apps, APIs, and agents to the internet with a strict pre-deploy audit and a preview → health-check → prod flow. Handles plain HTML/CSS/JS pages and static sites (Astro, Hugo, Jekyll, Eleventy, Vite) as well as Next, Remix, Nuxt, SvelteKit, FastAPI, Flask, Express, MCP servers, Claude Agent SDK scripts, Python workers, and Dockerized projects. Routes to free static hosts — Cloudflare Pages, Netlify, GitHub Pages, Render — or to Vercel, Railway, Docker+SSH VPS, or a cloudflared tunnel, and can also run the project locally. Use when the user says "/all-deploy", "/deploy", "/despliega", "deploy this", "ship this", "push to prod", "get this online", "publish my website", "sube mi página web", "publicar mi página", "hosting gratis", "free hosting", "custom domain", "dominio propio", "run it locally", "corre esto localmente", or otherwise asks to publish a site or project to a URL.

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Manage Alibaba Cloud Container Registry (ACR) Enterprise Edition using the @alicloud/cr20181201 TypeScript SDK. Use when working with container image registries on Alibaba Cloud, including instance management, namespaces, image repositories, image tags, build rules, image synchronization, security scanning, delivery chains, Helm charts, artifact lifecycle, and event notifications. Covers all 115 APIs of the CR 20181201 version.

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Manage Alibaba Cloud Elastic Compute Service (ECS) using the @alicloud/ecs20140526 TypeScript SDK. Use when working with cloud servers on Alibaba Cloud, including instance lifecycle (create, start, stop, reboot, delete), disks and snapshots, images, security groups, VPC networking, EIP, ENI, SSH key pairs, dedicated hosts, auto provisioning, launch templates, Cloud Assistant commands, tags, system events, diagnostics, storage capacity units, and prefix lists. Covers all 374 APIs of the ECS 20140526 version.

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See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

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Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.

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Critical Akka.NET best practices including EventStream vs DistributedPubSub, supervision strategies, error handling, Props vs DependencyResolver, work distribution patterns, and cluster/local mode abstractions for testability.

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[AUTO-INVOKE] MUST be invoked BEFORE writing or modifying any Solidity contract (.sol files). Covers private key handling, access control, reentrancy prevention, gas safety, and pre-audit checklists. Trigger: any task involving creating, editing, or reviewing .sol source files.

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Earnings analysis — pre- and post-earnings. Pre-earnings preview: prior-guidance review, recent-events tracking, last call's Q&A, and a key-things-to-watch framework for an upcoming release. Post-earnings: two tiers — a fast in-chat summary card (default) and a full Markdown research report (on request). Covers beat/miss, segments, margins, guidance, estimates, valuation. US / HK / A-share. Use whenever the user wants an earnings preview or a post-earnings / quarterly-results writeup. Triggers: "earnings update", "quarterly results", "Q1/Q2/Q3/Q4 results", "earnings report", "post-earnings analysis", "beat/miss", "guidance update", "earnings preview", "pre-earnings", "what to watch this earnings", "before earnings", "财报分析", "业绩更新", "季度业绩", "季报", "年报", "盈利分析", "财报点评", "财报前瞻", "业绩前瞻", "财报预览", "上季度指引", "財報分析", "業績更新", "季度業績", "季報", "年報", "財報點評", "財報前瞻", "業績前瞻", "財報預覽".

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Day Open protocol. Collects yesterday's commits, issues, notes, calendar, bot QA, Scout, world events — builds DayPlan and compact dashboard.

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Step-by-step execution of the OWC protocol with mandatory checkpoint at each step. Prevents skipping steps (including verification).

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Expert payment integration specialist mastering payment gateway integration, PCI compliance, and financial transaction processing. Specializes in secure payment flows, multi-currency support, and fraud prevention with focus on reliability, compliance, and seamless user experience.

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Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs, preventing budget overruns, optimizing spend, measuring ROI, or ensuring cost-effective AI operations.

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Expert error coordinator specializing in distributed error handling, failure recovery, and system resilience. Masters error correlation, cascade prevention, and automated recovery strategies across multi-agent systems with focus on minimizing impact and learning from failures.

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Use when verifying information (fact, number, quote, event, statement) against authoritative primary sources, or cross-checking a number via one-level metric decomposition (Z = P × Q). Triggers: "verify X", "is this true", "find the original source", "where is this number from", "two sources disagree", "is it true X never did Y". Covers five scenarios: (1) basic truthfulness check, (2) completeness / out-of-context quoting, (3) one-level reasoning verification, (4) negative-statement handling, (5) multi-source conflict side-by-side output. Dig into whitelisted primary sources only (user-supplied files, official websites & databases, authoritative industry sources); cited reports / charts / datasets must be downloaded and read locally to count as verified — if download is blocked, hand the link to the user. If nothing can be found, plainly state "cannot verify" rather than guessing, patching, or citing secondary paraphrases. Always reply in the user's question language.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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。

VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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。