「time」の検索結果

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。

Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.

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。

Maintain request-time claims enrichment, its public backend and parser APIs, gatekeeper and validator hooks, and the static claims-enrichment plugin. Excludes portal issuance-time transforms and token signing.

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。

Maintain host-independent persistent runtime state, its reusable directory parser, encrypted records and generated keys, portal and portal-free OAuth sessions, refresh/OIDC replay history, local identity epochs, restart E2E tests, and embedding lifecycle contracts.

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 modifying or reviewing Qwik Router code under packages/qwik-router, including runtime routing, buildtime route generation, middleware, adapters, SSG, markdown/MDX handling, or router tests.

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 when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.

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。

Personal AI Infrastructure (PAI) - PAI System Template MUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability. === CORE IDENTITY (Always Active) === Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas] Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend] Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.] Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context management Message to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.] === ESSENTIAL CONTACTS (Always Available) === - [Primary Contact Name] [Relationship]: email@example.com - [Secondary Contact] [Relationship]: email@example.com - [Third Contact] [Relationship]: email@example.com Full contact list in SKILL.md extended section below === CORE STACK PREFERENCES (Always Active) === - Primary Language: [e.g., TypeScript, Python, Rust] - Package managers: [e.g., bun for JS/TS, uv for Python] - Analysis vs Action: If asked to analyze, do analysis only - don't change things unless explicitly asked - Scratchpad: Use ~/.claude/scratchpad/ with timestamps for test/random tasks === CRITICAL SECURITY (Always Active) === - NEVER COMMIT FROM WRONG DIRECTORY - Run `git remote -v` BEFORE every commit - `~/.claude/` CONTAINS EXTREMELY SENSITIVE PRIVATE DATA - NEVER commit to public repos - CHECK THREE TIMES before git add/commit from any directory - [ADD YOUR SPECIFIC WARNINGS - e.g., iCloud directory, company repos, etc.] === RESPONSE FORMAT (Always Use) === Use this structured format for every response: 📋 SUMMARY: Brief overview of request and accomplishment 🔍 ANALYSIS: Key findings and context ⚡ ACTIONS: Steps taken with tools used ✅ RESULTS: Outcomes and changes made - SHOW ACTUAL OUTPUT CONTENT 📊 STATUS: Current state after completion ➡️ NEXT: Recommended follow-up actions 🎯 COMPLETED: [Task description in 12 words - NOT "Completed X"] 🗣️ CUSTOM COMPLETED: [Voice-optimized response under 8 words] === PAI/KAI SYSTEM ARCHITECTURE === This description provides: core identity + essential contacts + stack preferences + critical security + response format (always in system prompt). Full context loaded from SKILL.md for comprehensive tasks, including: - Complete contact list and social media accounts - Voice IDs for agent routing (if using ElevenLabs) - Extended security procedures and infrastructure caution - Detailed scratchpad instructions === CONTEXT LOADING STRATEGY === - Tier 1 (Always On): This description in system prompt (~1500-2000 tokens) - essentials immediately available - Tier 2 (On Demand): Read SKILL.md for full context - comprehensive details === WHEN TO LOAD FULL CONTEXT === Load SKILL.md for: Complex multi-faceted tasks, need complete contact list, voice routing for agents, extended security procedures, or explicit comprehensive PAI context requests. === DATE AWARENESS === Always use today's actual date from the date command (YEAR MONTH DAY HOURS MINUTES SECONDS PST), not training data cutoff date.

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。

Voice a papercut reel and time it to the picture. Three paths, local Qwen3-TTS, your own recording or another TTS, or a placeholder voice. Covers delivery rules, voice.json, captions and scene timing. Use for "set up the voice", "re-voice this", "time the script".

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for CI/CD, registry, dependency drift, artifact provenance, image build, release pipeline, and runtime consumer challenges. Use when the user asks to trace dependency drift, registry pulls, malicious packages, build or release tampering, CI execution, artifact signing, or which shipped artifact the runtime actually consumes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for source maps, build manifests, chunk registries, emitted bundles, obfuscated loader flow, and frontend runtime recovery. Use when the user asks to reconstruct served JavaScript structure, inspect source maps or chunk maps, trace bundle loading, recover hidden routes or APIs from emitted assets, or explain runtime behavior from built frontend artifacts. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Manage scheduled jobs. Use when the user wants to create, list, inspect, update, pause, resume, or remove recurring or one-time scheduled tasks. Handles cron schedules, interval-based (every), one-time (at) jobs, platform job templates, and scheduled workflow runs.

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。

ActivityWatch is a privacy-first, open-source automated time tracker that records application usage, browser activity, and AFK status across Windows, macOS, and Linux. With 16k+ GitHub stars, it provides detailed productivity analytics without sending data to external servers.

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。

Agno is a high-performance Python framework for building, running, and managing agentic software at scale. It provides a three-layer architecture — framework, runtime, and control plane — enabling developers to go from agent prototype to production API in roughly 20 lines of code.

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 the user says 'set up respira', 'respira not connecting', 'check my respira connection', or 'fix respira'. Walks through first-time setup and diagnoses connection failures: timeouts, 401s, 403s, and plugin or server version mismatches.

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。

Interactive code simulation engine that spawns ghost personas to review your code before it ships. Each ghost walks through your code line-by-line from a different failure perspective: The Adversary (race conditions, double-submit, idempotency), The Enterprise Edge (business logic gaps, multi-currency, B2B tax exemptions, locale), Chaos Monkey (timeouts, partial failures, network partitions, OOM). Produces a chaos timeline, structured bug report with severity ratings, and three resolution tiers (quick fix, robust architecture, generated test suite). Use this skill whenever the user mentions code review, PR review, "find bugs", "what could go wrong", "will this break", "is this safe", "stress test", "edge cases", design review, pre-merge check, dry run, chaos test, or wants a second opinion on any code — even if they don't explicitly ask for "ghost personas" or "simulation". Also trigger when someone pastes a code snippet with any question about its correctness or safety.

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。

Trace execution time of Python method invocations in a live process with call stack visualization. Use this to see a hierarchical call tree showing which sub-calls are slow and where time is spent within a function.

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。

Display input/output args, return object and cost time of a Python method invocation in a live process. Use this to observe function behavior at runtime — see what arguments go in, what comes back, and how long it takes. This is the most frequently used diagnostic command.

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 intraday volatility dynamics with open/close effects, lunch-time patterns, and event-driven volatility estimation. Use when modeling intraday volatility, timing order execution, or analyzing time-of-day effects.

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 institutional flow patterns with fund flow analysis, positioning data, and sentiment indicator synthesis. Use when analyzing market flows, tracking institutional positioning, or assessing market sentiment.

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。

Customer feedback analysis — sentiment detection, NPS/CSAT frameworks, feature request clustering, support ticket triage, churn signal detection, and feedback-to-roadmap translation

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 analyzing published content (blog posts, social media, newsletters) for sentiment, structural quality, hook effectiveness, readability, topic classification, and engagement correlation. Invoke for daily post analysis, content audits, or engagement driver identification.

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。

Evaluate HackerOne / Bugcrowd / Intigriti programs before committing time. Decide signal-to-noise, payout history, response time, scope size, and competition level. Use when the user is considering a new bug bounty target or asking "should I hunt this".

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。

This skill should be used when the user asks to "build a scroll animation", "add ScrollTrigger", "pin a section while scrolling", "scrub an animation to scroll", "create a hero timeline", "do a horizontal scroll section", "split text and animate words", "animate a layout change with GSAP Flip", "sync ScrollTrigger with Lenis", "Lenis smooth scroll jittery", "ScrollTrigger markers drift", "ScrollTrigger pins break with Lenis/Locomotive", or "set up smooth scroll with GSAP pinning". Covers GSAP timelines, ScrollTrigger, SplitText, Flip, and Lenis/Locomotive smooth-scroll sync for code-driven web motion.

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。