「filing」の検索結果

Comprehensive OSINT methodology skill for offensive security, red team intelligence gathering, and bug bounty reconnaissance. Covers domain recon, email harvesting, social media profiling, GitHub/code leaks, Shodan/Censys enumeration, breach data lookup, employee profiling, infrastructure mapping, cryptocurrency tracing, geospatial intelligence, and AI-assisted analysis workflows. Use when performing reconnaissance against a target domain or organization, investigating a person or entity, tracing cryptocurrency flows, geolocating images or events, or building an attack-surface map.

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Kick off public shotgun metagenomics QC, host-depletion, taxonomic profiling, and functional profiling workflows using nf-core/taxprofiler, Kraken2, Bracken, MetaPhlAn, and HUMAnN.

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。

Guide performance profiling for Apple platform apps with Instruments, Xcode diagnostics, and MetricKit. Use when investigating app hangs, stutters, high CPU, memory leaks, memory growth, OOM crashes, slow launch, battery drain, thermal issues, App Store performance readiness, or when adding os_signpost and measurement hooks.

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。

Analyze Chrome, Chromium, Electron, React DevTools, or Perfetto-compatible JSON traces and audit user-reported profiling findings without loading large artifacts into context; prove trigger-to-render/layout chains, separate measured facts from source inference, find exact code choke points, classify forced layout and render fanout, implement semantically safe fixes, and verify behavior plus repository budgets. Use for trace files, reported profiling durations or call chains, dropped frames, long tasks, resize or scroll jank, render storms, layout thrashing, selector hot paths, interaction latency, or requests to locate exact source-level bottlenecks.

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。

Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while `samber/cc-skills-golang@golang-performance` provides the optimization patterns.

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。

Marker gene-based taxonomic profiling using MetaPhlAn 4. Provides accurate species-level relative abundances using clade-specific markers. Use when accurate taxonomic profiling is needed and computational resources are limited, or for comparison with HMP/other MetaPhlAn studies.

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。

Prepare for China's annual individual income tax reconciliation (个税年度汇算): check income, deductions and special additional deductions, compare the two treatments of a year-end bonus, and estimate the refund or amount to pay before filing in the 个人所得税 app. Use when asked 个税汇算怎么弄, 年终奖单独计税还是合并, 我能退多少税, 专项附加扣除, or how does China's annual tax reconciliation work. Produces a filing checklist, the deductions the person may be missing, a bonus comparison, the estimate with workings, and deadlines. Not tax advice.

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。

Pull company financials, SEC filings, and analyst consensus for a public company. Use this skill whenever the user says "10-K", "10-Q", "earnings", "revenue of", "financials for", "analyst rating for", "price target for", or provides a stock ticker. Combines SEC EDGAR for official filings with Yahoo Finance / TipRanks for analyst data. Search + scrape only; no interact needed.

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。

Profiles RNA-binding protein targets without antibody or UV crosslinking using STAMP (APOBEC1-RBP fusion, C-to-U editing), scSTAMP (single-cell), TRIBE/HyperTRIBE (ADAR-RBP, A-to-I editing), DART-seq (APOBEC1-YTH for m6A), or Bullseye/SAILOR edit-site detection pipelines. Use when antibody is unavailable or specificity is doubtful, when single-cell RBP profiling is needed (scSTAMP), or when in vivo RBP profiling without UV is preferred.

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Expert blueprint for performance profiling and optimization (frame drops, memory leaks, draw calls) using Godot Profiler, object pooling, visibility culling, and bottleneck identification. Use when diagnosing lag, optimizing for target FPS, or reducing memory usage. Keywords profiling, Godot Profiler, bottleneck, object pooling, VisibleOnScreenNotifier, draw calls, MultiMesh.

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。

Expert debugging and profiling for leaks, GPU/Visual Profiler, headless CI QA, orphan nodes, thread-safe logs, and custom Debugger monitors — not print/breakpoint tutorials. Trigger on OBJECT_ORPHAN_NODE_COUNT, ObjectDB growth, Visual Profiler GPU spikes, flaky headless exits, or remote device consoles. Keywords: orphan nodes, Performance.get_monitor, Visual Profiler, Time.get_ticks_usec, EditorDebuggerPlugin, headless QA, push_error, backtrace.

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。

Guide performance profiling with Instruments, diagnose hangs, memory issues, slow launches, and energy drain. Use when reviewing app performance or investigating specific bottlenecks.

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。

When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.

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 dotnet-diagnostics-mcp for MCP-driven .NET CPU, allocation, GC, and test-host profiling. USE FOR: profiling unit tests or investigating runtime bottlenecks. DO NOT USE FOR: writing test assertions, coverage collection, or precise microbenchmark timing. INVOKES: connect the MCP server, select target processes, collect bounded profiles, and attribute hotspots to source.

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 the open-source free `Asynkron.Profiler` dotnet tool for CLI-first CPU, allocation, exception, contention, and heap profiling of .NET commands or existing trace artifacts. USE FOR: Asynkron.Profiler setup; automation-friendly profiling output; CPU, allocation, exception, contention, and heap investigation. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are 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。

Query and analyze SEC filings and financial statements using EdgarTools. Get company data, filings, XBRL financials, and perform multi-company analysis.

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。

Background context for housing loan tax credit (住宅ローン控除) in the shinkoku tax filing plugin. Contains eligibility requirements, credit limits, calculation rules, and interaction with furusato-nozei for the current tax year. This skill is not user-invocable — Claude loads it automatically when responding to housing loan tax credit questions or calculations.

Background context for invoice-system input tax credit rules (仕入税額控除) in the shinkoku tax filing plugin. Contains eligibility requirements, the 6 permanent exceptions (帳簿のみ保存の恒久特例), transitional measures for purchases from tax-exempt businesses, and storage requirements. This skill is not user-invocable — Claude loads it automatically when responding to input tax credit questions under the invoice system.

This skill should be used when the user needs to know what documents to collect for their tax filing, wants a checklist of required documents, or asks where to obtain specific tax documents. Trigger phrases include: "必要書類", "書類を集める", "何を準備すればいい", "源泉徴収票はどこで", "書類チェックリスト", "確定申告に必要なもの", "書類収集", "準備するもの".

Use when you need to CAPTURE / PRODUCE XProf (jax.profiler) profiling artifacts from sgl-jax (SGLang on JAX/TPU) for later performance analysis: driving a live server (/start_profile, stage-separated prefill/decode), offline bench_one_batch --profile, or kernel microbench. This skill produces the trace files; it does not analyze them.

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。

Profiles Python code for performance bottlenecks and memory issues. Use when Python code is slow or when profiling for optimization before a release.

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。

Colorado Privacy Act (CPA) compliance implementation. Covers universal opt-out mechanism required since July 2024, profiling opt-out rights, sensitive data consent requirements, AG rulemaking under 4 CCR 904-3, and consumer rights framework. Effective July 1, 2023.

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Implements GDPR Art. 22 automated decision-making and AI Act Art. 14 human oversight requirements for AI systems. Covers identification of solely automated decisions, meaningful human intervention design, logic explanation mechanisms, and contestation procedures. Keywords: Art. 22, automated decision, human oversight, AI Act, profiling, contestation.

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。

Institutional-grade equity research skills for AI agents. 80 Claude-type skills across 14 verticals (equity-research-core, models-and-pitches, bio-pharm, scenarios, quantitative-analysis, idea-generation, options-derivatives, business-intelligence, industry-analysis, macro-strategy, portfolio-strategy, technical-analysis, risk-and-psychology, trading-as-business) powered by agentii.ai's agent-use-ready SEC filing data plane — SEC filings and 15K+ earnings call transcripts, 15.99M XBRL facts, and company profiles for 1,146+ US-public-equity tickers. Features the three-layer retrieval protocol (Document Discovery → Page Map → Deep Read, with deep-outline escalation) — measured, not asserted: 97.5% saved against a sequential read, and the page map itself is 10.0% of one (spec 062 T030, 2026-09-23) — server-side parallel multi-period search via search_cross_period, a full Excel/PPT generation pipeline with 3-tier office backend support, and the spec-046 governance layer (constitution, thesis and single-skill modes, mechanical gates, and a template-owned disclaimer on generated reports).

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。