「ace」の検索結果

Hunt ASP.NET-specific surface — ViewState deserialization (signed-only vs encrypted), machineKey recovery, dual-parser MAC-bypass anti-pattern, request-validator bypass, trace.axd/elmah.axd disclosure, load-balanced ViewState cross-node failures, SafeControl enumeration via reflection, customErrors mode=Off stack-trace leaks, classic Webforms .aspx/.asmx/.svc surface. Built for ASP.NET Webforms + WCF + SharePoint farms.

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。

Econometrics skill for Synthetic Control Method (SCM). Activates when the user asks about: "synthetic control", "SCM", "synthetic counterfactual", "donor pool", "placebo test", "in-space placebo", "in-time placebo", "MSPE ratio", "Abadie Diamond Hainmueller", "augmented synthetic control", "penalized SCM", "synthetic DID", "合成控制", "合成控制法", "捐助池", "安慰剂检验", "合成反事实", "合成DID", "政策评估"

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 Hugging Face Hub (huggingface_hub) release notes from cached PR JSON files. Use when asked to draft release notes from PR files.

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。

Create, convert, or repair one Tutti workspace app as either a self-contained publishable package under package/ or a Chrome-style local debug app under .tutti/dev-app/. Use for mention://workspace-app-factory/create handoffs, mention://workspace-app-factory handoffs, standalone app generation, adapting existing repositories, Load unpacked repair flows for invalid local project directories, tutti.app.json and tutti.cli.json manifests, bootstrap.sh scripts, package-local AGENTS.md, local HTTP runtimes, TUTTI_APP_* host/port/storage rules, healthchecks, app assets, i18n, validation, and optional Tutti CLI integration.

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 asks to "track where my emails are actually landing after I send", "read my seed-list inbox vs spam vs promotions results", "trend my Gmail Postmaster / Microsoft SNDS reputation", or "did placement drop after my last send"; produces a per-provider inbox/spam/promotions placement read, a domain/IP reputation trend from Postmaster + SNDS, a send-over-send delta with named regressions, and a reusable SEND-S placement snapshot on your own exported telemetry. Not for the pre-send SPF/DKIM/DMARC auth pre-flight — use deliverability-qa; not for computing the EQS or running the vetoes — use email-quality-auditor. 邮件收件箱落点监测/收件箱vs垃圾邮件/Postmaster声誉趋势

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 asks to "build my brand-safety exclusion lists", "set placement / topic / content exclusions before launch", "add network and audience exclusions", or "prep the A1 brand-safety evidence for the auditor"; produces a placement/network exclusion list, a content-suitability & sensitive-topic block list, an audience/negative-audience exclusion set, and a packaged A1 brand/placement-safety evidence file for the gate. Not for building the audiences you target — use audience-segment-builder; not for computing the RQS or issuing the A1 verdict — use ad-account-auditor. 品牌安全/排除位置/否定受众列表

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 measuring or improving agent quality and performance — set up evaluators, online monitoring, CI/CD quality gates, observability, or cost optimization. Triggers on: "evaluate my agent", "add evaluator", "measure quality", "quality gate", "run evals", "agent too slow", "why is it slow", "reduce latency", "set up observability", "CloudWatch dashboard", "how much does my agent cost", "cost optimization", "logs not showing up", "logs missing", "spans not found", "eval failing", "eval error", "dev traces", "local traces", "agentcore dev traces", "traces to CloudWatch". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.

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。

Connects AI agents to remote Windows desktop applications on Amazon WorkSpaces Applications (AppStream 2.0) through the managed Agent Access MCP server, and guides reliable desktop automation. Covers connecting an agent to the MCP endpoint (SigV4, streaming URL, and Active Directory SAML/Domain Join), BLOCKING vs POLLING connect modes, the computer-use tools (screenshot, click, type, key, scroll), screenshot-budget and action-batching discipline, MCP tool forwarding (forwarded___ tools), session lifecycle and expire-on-delete, and troubleshooting connection errors. Use when building or debugging an agent that drives a remote Windows desktop or GUI application via WorkSpaces Applications / AppStream — including "dcv session not ready", "client_disconnected", 400 signing-region, POLLING/connection_status, SAML assertion, or forwarded tool questions. Not for Amazon WorkSpaces Personal/Core virtual desktops or general AppStream fleet administration unrelated to agent access.

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。

Builds, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging or threat detection.

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。

Draw a testable attack surface from one authorized target URL or one application. Use when the user says 攻击面, 供给面, 画攻击面, map the surface, application recon, find the business host, JS inventory, or when the only visible page is login. Derive hosts, APIs, keys, and the object graph from what the app already exposes. Do not open with directory brute or payload spray. Use when the user runs /attack-surface-mapping.

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 asks to review, verify, or audit a report, manuscript, or analysis in the workspace for traceability — resolving citations, flagging numbers with no source, and checking figures against the code that generated them. Emits a structured review block the app renders as reviewer findings. Verifies traceability, never "correctness".

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。

Discovers, searches, and installs skills from multiple AI agent skill marketplaces (400K+ skills) using the SkillKit CLI. Supports browsing official partner collections (Anthropic, Vercel, Supabase, Stripe, and more) and community repositories, searching by domain or technology, and installing specific skills from GitHub. Use when the user wants to find, browse, or install new agent skills, plugins, extensions, or add-ons; asks 'is there a skill for X' or 'find a skill for X'; wants to explore a skill store or marketplace; needs to extend agent capabilities in areas like React, testing, DevOps, security, or APIs; or says 'browse skills', 'search skill marketplace', 'install a skill', or 'what skills are available'.

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 a custom browser-based annotation interface tailored to your data for reviewing LLM traces and collecting structured feedback. Use when you need to build an annotation tool, review traces, or collect human labels.

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。

Governs the Claude Code/Codex Skill surface: reconciles source/install/catalog-visibility drift without losing cold capability. Use when users ask how many Skills load, why the catalog is truncated, want routers visible while other bundles stay cold, or need duplicate/superseded-Skill or old-cache cleanup. Not for building a marketplace manifest (use marketplace-dev) or repo audits (use marketplace-health-check).

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。

Runs a 6-dimension evidence-based health audit of this skills marketplace repo — code safety, docs/SSOT, security/PII, PR/issue triage, manifest integrity — via a parallel workflow, then verifies findings by priority. Use for 全面体检 / 检查仓库状态 / 审计一下仓库, a pre-release sweep, or "is this repo OK" even without saying "workflow". Not for building marketplace.json (use marketplace-dev) or cache drift (use skill-governance).

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, improve, and review interfaces for websites, apps, dashboards, and components: explore distinct design directions, compare styles side by side, and refine visual hierarchy against real screenshots. Delivers comparison pages, design notes, mockups, or working interfaces. Use for new interface design, style comparison, visual polish, screenshot recreation, or interface review. Not for business logic, APIs, builds, or code cleanup without visible UI changes. If oil-ui-pro is installed, use oil-ui-pro instead. 设计、改进和评审网站、App、后台与组件的界面，完成设计方向探索、多风格同屏比较、视觉层级和基于实际画面的迭代；按请求交付对比页、设计说明、设计稿或可运行界面。当用户需要新界面设计、比较不同设计风格、视觉精修、截图还原或界面评审时使用。只负责设计判断，组件归属、数据流、状态正确性和测试等代码实现质量不在范围内。不用于纯业务逻辑、接口、构建部署、无界面行为变化的代码整理、单独绘制普通插画或操作现有网站。已安装 oil-ui-pro 时交给 oil-ui-pro。

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。

Verify your Hugging Face account and search the model hub. Read-only. Trigger phrases: hugging face, huggingface, hf model, search models.

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。

Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.

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。

E-commerce SEO analysis: Google Shopping visibility, Amazon marketplace intelligence, product schema validation, competitor pricing analysis, and marketplace keyword gaps. Combines on-page product SEO with marketplace data from DataForSEO Merchant API. Use when user says "ecommerce SEO", "product SEO", "Google Shopping", "marketplace SEO", "product schema", "Amazon SEO", "product listings", "shopping ads", or "merchant SEO".

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。

Discover OPC UA servers, connect MATLAB clients, and browse/navigate server nodes using opcuaserverinfo, the Local Discovery Service (LDS), opcua, connect, setSecurityModel, certificate-trust functions, findNodeById, opcuanode, and Namespace/Children traversal. Use when finding OPC UA servers on the network, querying endpoints and security policies, connecting to a server, authenticating with username/password or certificates, configuring security modes, handling certificate-trust or hostname-mismatch errors, troubleshooting failed connections or empty discovery, inspecting an OPC UA certificate (.der/.pem), browsing an address space, finding nodes by name or NodeId, navigating node hierarchies, invoking method nodes, or batch-processing large namespaces. Trigger on: opcuaserverinfo, LDS, opcua, opc.ua.Client, setSecurityModel, opc.ua.trustServerCertificate, OPC UA certificate, findNodeById, opcuanode, browse OPC UA, find node, OPC UA namespace, OPC UA method node, Industrial Communication Toolbox.

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。

Perform aerospace unit conversions, time conversions, coordinate frame transformations, and rotation representations using Aerospace Toolbox. Use when converting units (length, velocity, angle, acceleration, angular velocity, force, mass, pressure, temperature, density), computing Julian dates or decimal years, transforming between coordinate frames (ECEF, ECI, LLA, flat Earth, geodetic/geocentric, NED, body, wind, stability), or working with rotation representations (Euler angles, DCM, quaternion, Rodrigues vector). Also use when the user asks about aerospace coordinate systems, reference frames, or rotation conventions.

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 driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface extraction, 3D asset generation, static-object placement, point-cloud georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization — route those to matlab-import-driving-data.

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。

Given a Japanese NLP GitHub repo/model/dataset (URL / owner/repo / tool name) OR a topic, find what's already in awesome-japanese-nlp-resources and discover related resources NOT yet listed (contribution candidates). Mines the bundled dataset, then expands via web research across GitHub and Hugging Face. Use when the user names a SPECIFIC repository, model, or tool and wants alternatives/equivalents, OR wants to discover Japanese NLP resources for a topic that are NOT yet in the list, OR wants to prepare a contribution. Trigger phrases include 'mecabに似たツール', 'fugashiの代替', 'alternatives to fugashi', 'repos like manga-ocr', 'what else is like sudachi', 'リストに無い新しい日本語NLP', 'awesome-japanese-nlpに追加できそうな', '最近公開された日本語NLPツール', 'find unlisted Japanese NLP repos', 'new Japanese models on Hugging Face', 'contribute a new resource'. For a simple lookup of what already exists, use the search skill instead.

Search all Japanese NLP resources (libraries, models, datasets, tutorials, dictionaries, Hugging Face). Accepts keywords or natural language questions in any language. Use whenever the user asks which Japanese NLP resource to use, or wants to find one: tokenizers / morphological analyzers, BERT or LLM models, embeddings, NER, text classification, datasets / corpora, dictionaries, tutorials, or Hugging Face models. Trigger phrases include '日本語の形態素解析ライブラリ', 'おすすめの日本語tokenizer', '日本語BERTモデル', '日本語の感情分析データセット', '日本語LLM 一覧', 'which Japanese embedding model', 'Japanese NER library'.