「tia」の検索結果

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

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 flow cytometry data with FlowKit, including spillover compensation, logicle and biexponential transforms, hierarchical gating, GatingML strategies, and supported FlowJo 10 workspaces. Use for reproducible gate counts, population percentages, gated fluorescence summaries, or reproducing a FlowJo analysis in Python. For FCS metadata inspection or file-format repair alone, use FlowIO.

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。

Retrieves and analyzes Cancer Dependency Map (DepMap) release data, including CRISPR Chronos gene effects, cancer model annotations, omics biomarkers, and PRISM drug sensitivity. Supports cancer-selective dependency, co-essentiality, and candidate synthetic-lethality analyses with release-aware identifiers and statistical checks.

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。

Draft or restructure scientific manuscript arguments, sections, and initial-submission materials from author-provided evidence. Use for 论文写作、章节起草、论证重构、正文压缩、首次投稿材料. Use nature-polishing for language-only edits to existing prose and nature-response for post-decision correspondence.

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。

Draft, audit, or revise responses to peer review, revision cover letters, and marked-manuscript or LaTeX revision packages. Use for 审稿意见回复、逐点回复、返修信、 rebuttals and edits to existing response drafts. Initial-submission materials belong to nature-writing; simulated peer review belongs to nature-reviewer.

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。

Azure Communication Services common utilities for Java. Use when working with CommunicationTokenCredential, user identifiers, token refresh, or shared authentication across ACS services.

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。

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data 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。

Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.

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。

Authorized multi-stage attack-path planning and orchestration spanning reconnaissance, initial access, privilege escalation, lateral movement, and reporting. Entry point for full engagements and cross-phase operations.

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。

Core UI/UX engineering skill for building highly interactive, spatial, weightless, and glassmorphism-based web interfaces using GSAP and 3D CSS.

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。

Access matrix of role-by-module permissions, with per-role scope, confidentiality level and SME tier, as CSV, SQL, JSON Schema or Notion on request. Use for access reviews.

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。

Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and domain dominance for red team operations and penetration testing.

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。

Replace the manual commit-by-commit classification step in `breeze release-management prepare-provider-documentation` with AI-driven classification. For each provider with pending changes, analyze every PR (batched into one sub-agent per provider, not one per PR), pay special attention to potentially breaking changes by inspecting the actual diff, scope multi-provider PRs to the current provider's slice, ask the release manager when uncertain, and apply version bumps + changelog entries. Use during the regular provider release cycle as an alternative to the interactive breeze prompts.

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。

CCXT command-line interface (ccxt-cli) for interacting with 100+ cryptocurrency exchanges directly from the terminal — no code required. Covers installing the CLI, calling any unified CCXT method (fetchTicker, fetchOHLCV, createOrder, fetchBalance), passing arguments and exchange-specific params, authenticating with API keys, sandbox/testnet mode, streaming live tickers and orderbooks over WebSocket, plotting OHLCV charts, and scripting with raw JSON output. Use when the user wants to query an exchange, test API credentials, place or inspect orders, or debug exchange requests from the command line or in shell scripts.

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。

Run agent-browser on AWS Bedrock AgentCore cloud browsers. Use when the user wants to use AgentCore, run browser automation on AWS, use a cloud browser with AWS credentials, or needs a managed browser session backed by AWS infrastructure. Triggers include "use agentcore", "run on AWS", "cloud browser with AWS", "bedrock browser", "agentcore session", or any task requiring AWS-hosted browser automation.

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 firmware images, partition tables, boot chains, update packages, extracted filesystems, embedded configs, and device-facing trust boundaries. Use when the user asks to unpack firmware, map partition layout, inspect bootloader or init chains, recover update keys or credentials, trace config loading, or explain how a device surface reaches the decisive artifact. 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 parser differentials, HTTP normalization gaps, ambiguous headers, path decoding drift, transfer-framing mismatches, and request smuggling routes. Use when the user asks to trace proxy and backend parse differences, conflicting path normalization, Host or forwarded-header ambiguity, CL/TE issues, or routing outcomes that differ across hops. 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 Active Directory, Kerberos, LDAP, OAuth, enterprise messaging, Windows host forensics, credential material, and lateral-movement challenges. Use when the user asks to trace tickets or tokens, inspect mailbox rules, analyze Windows host evidence, understand an AD trust path, or explain a lateral-movement chain across sandbox-linked nodes. 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。

Use for authorized multi-stage attack-path planning and orchestration when a task spans reconnaissance, initial access, privilege escalation, lateral movement, or impact assessment. Route single-stage tasks directly to their specialist skill.

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 authorized reverse engineering of browser extensions (Chrome/Firefox) including manifest analysis, background workers, and extension-based credential or traffic logic recovery.

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 making UI/frontend changes guided by visual context, when the user selects elements visually, draws annotations, or provides screenshots alongside change requests. Also use when editing components where spatial context (element identity, DOM references, layout data) supplements text instructions.

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 competition, identify differentiation opportunities, and develop winning market positioning strategies using Porter's Five Forces, Blue Ocean Strategy, and positioning maps. Use this skill when evaluating competitors, assessing market positioning, identifying sustainable competitive advantages, or preparing competitive strategy analysis for a startup or investor pitch.

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。

Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.

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。

Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.

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。