「poi」の検索結果

Plan a feature before writing any code. Use this skill at the START of non-trivial feature work — when the user says they want to "add", "build", "implement", "create", "develop", or "ship" a feature, endpoint, component, page, service, or capability. Especially trigger when the user's prompt is short or under-specified ("add a dashboard", "build an auth flow", "let's do user activity reports") — those need planning, not direct execution. The skill walks through requirements clarification, codebase exploration, sketches a Mermaid architecture/flow diagram of the proposed design, and produces a plan.md document the user can hand off to a fresh AI session for execution. Skip only when the change is genuinely trivial (typo fixes, single-line tweaks, renames). When in doubt, plan.

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 provides expert-level guidance for VS Code extension development. Use when implementing new extension features, debugging extension code, designing WebView UIs, implementing Language Server Protocol features, or optimizing extension performance. Covers activation events, contribution points, VS Code API patterns, security best practices, testing strategies, and publishing workflows.

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。

Hunts for Windows persistence across autostart locations: Run keys, services, scheduled tasks, WMI event subscriptions, and startup folders, baselining them to surface anomalous or recently added entries. Activates for requests to hunt persistence, audit autostart extensibility points, or find malware autoruns on Windows.

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。

Manually unpacks a runtime-packed Windows binary by finding the original entry point (OEP) through tail-jump and entropy analysis, then guiding a memory dump at OEP. Activates for requests to manually unpack a sample, find the OEP, or unpack a custom/unknown packer that generic tools cannot handle.

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。

Captures and analyzes malware network traffic from a detonation: extracting C2 endpoints, HTTP/DNS patterns, TLS metadata (JA3/SNI), and beaconing from a PCAP to build network IOCs and detection. Activates for requests to analyze malware PCAP, extract C2 from traffic, or study network 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。

Analyzes cryptojacking/coinminer malware by extracting mining pool endpoints (stratum), wallet addresses, algorithm and miner identifiers (XMRig and forks), and persistence or resource-control settings from static strings and config. Activates for requests to analyze a cryptominer, extract mining pool and wallet IOCs, or identify coinminer configuration.

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 Java/JAR malware (such as Adwind/jRAT-class cross-platform RATs) by inventorying the archive, reading the manifest entry point, detecting obfuscators and string encryption, and flagging suspicious runtime, reflection, and networking class usage. Activates for requests to analyze a malicious JAR, inspect Java malware, or identify a Java RAT.

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。

Rebuilds a usable PE file from a memory dump by fixing the section alignment (virtual-to-raw), correcting the entry point, and preparing for import table reconstruction. Activates for requests to rebuild a dumped PE, fix a memory-dumped executable, or convert a process dump into an analyzable file.

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 process injection in a memory image by identifying private executable regions with no file backing, RWX protections, and modified entry points using Volatility 3 malfind-style analysis. Activates for requests to detect process injection, find injected code in memory, or triage suspicious executable regions in a memory image.

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。

Entry point for documentation skills covering Upstash Search quick starts, core concepts, and TypeScript SDK usage. Use when a user asks how to get started, how indexing works, or how to use the TS client.

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。

Fast serverless inference on Fireworks AI — open models, fine-tuning, and function-calling optimized endpoints.

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。

FastAPI guidance — typed endpoints, Pydantic validation, dependency injection, async patterns, and production deployment.

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 operate endpoint detection and response — policy tuning, behavioral detections, threat hunting, and response actions.

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 data loss prevention — data discovery, classification, policy enforcement across endpoint, network, and cloud.

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。

Keep long conversations coherent — summarization checkpoints, entity tracking, topic stacks, and graceful context handoffs. Use when dialogues run long or span sessions and the agent keeps losing the thread.

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。

Idiomatic modern C++: RAII, smart pointers, move semantics, value semantics, STL algorithms, and safe concurrency. Use when writing, reviewing, or structuring C++ 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。

Designing clinical trials — phases, randomization, endpoints, sample size, and CONSORT-compliant reporting.

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。

Build and apply brand guidelines — voice, visual identity, and usage rules that keep every touchpoint consistent.

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。

Complete B2B SaaS marketing agency powered by 90 AI agents across 17 specialties. This is the entry point for ALL marketing requests. Routes to the right specialist team: content marketing, SEO, paid media, social media, email marketing, design, sales enablement (including technical presales — demos, proofs of concept, security questionnaires), product marketing, account-based marketing (ABM), partnerships and channel programs (co-marketing, marketplace GTM, channel conflict and deal registration, partner economics), growth, analytics, project management, or client operations. Use this skill when the request spans multiple disciplines or when unsure which specialist to invoke. Also triggers on: marketing help, marketing team, marketing agency, what can you do, marketing capabilities.

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。

Reviews audio DSP code for numerical correctness. Use when the user asks to review, audit, or check DSP code for correctness issues — filters, feedback loops, fixed-point arithmetic, accumulation loops, or any numeric computation in audio code. Trigger on "check this filter for NaN", "why does my reverb blow up?", "is this numerically stable?", "why do I hear DC in my output?". Pairs with audio-dsp-review (realtime safety); this skill covers numeric correctness. Flag issues proactively.

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。

pyfixest demeaner_backend="cupy64" (including its CPU fallback when cupy is absent) is NOT numerically identical to the default numba backend and does NOT drop fully-absorbed/collinear regressors the same way. Use when: (1) adding demeaner_backend="cupy64" to existing pf.feols/fepois calls changes the printed coefficient table, (2) a regression report suddenly gains rows with absurd estimates (e.g. coef 435.8, SE 7106) for controls absorbed by the fixed effects, (3) diffing outputs before/after a backend change, or (4) anything parses a pyfixest text report by line position.

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。

Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend="cupy64" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT.

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。

Security-first code review & vulnerability prevention (IDOR, XSS, CSRF, SSRF, SQLi, Auth/JWT, Mass Assignment, Sensitive Data Exposure). Use when writing web features, designing endpoints, or auditing security.

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。

Dispatch and execute implementation plans with TDD and checkpoints. Use when plan is ready. Parallel by default for independent tasks.

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。