「ace」の検索結果

Automate headless CMS operations in Contentful -- list spaces, retrieve space metadata, and update space configurations through the Composio Contentful 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。

Coordinate several coding agents in parallel through Superset, each in its own workspace, with follow-ups, progress reads, dependency tracking, and structured results. Use when the user asks to delegate, parallelize, fan out, or split up coding work across agents, workspaces, or hosts, hand work between agents, or monitor workers, including "spin up agents for each of these", "run these in parallel", "what are my workers doing". Not for ordinary single-agent workspace, task, or automation management.

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。

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

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。

Parses error messages, traces execution flow through stack traces, correlates log entries to identify failure points, and applies systematic hypothesis-driven methodology to isolate and resolve bugs. Use when investigating errors, analyzing stack traces, finding root causes of unexpected behavior, troubleshooting crashes, or performing log analysis, error investigation, or root cause 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。

Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for 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。

Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.

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 this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process 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。

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

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 about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.

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 this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.

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 evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals 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。

Manage GSD workspaces — create, list, or remove isolated workspace environments

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。

Audit Meta Ads measurement, Pixel and Conversions API, attribution, Facebook and Instagram creative, audiences, placements, automation, budgets, account structure, and policy. Use for Meta Ads, Facebook Ads, Instagram Ads, Advantage+, Pixel, CAPI, Events Manager, creative fatigue, or Meta campaign optimization.

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 matter workspaces for multi-client practices — create, list, switch, close, or detach the active matter. Use when the user wants to create a new matter workspace, switch the active matter, list matters, archive a matter, or work at practice-level only without an active matter.

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。

Route OpenClaw design work to canonical brand, Carapace product-interface, marketing-page, or design-audit guidance. Use when a task touches OpenClaw visual identity, shared CSS tokens, product UI, public web pages, or Carapace compliance.

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。

Workspace Git identity and credential management. ALWAYS invoke this skill when the user asks about configuring Git user info, adding HTTPS tokens, importing SSH keys, or managing workspace-level Git authentication.

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。

Graceful degradation workflow for ffmpeg encoding failures with progressive fallback strategies

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。

Review auto-memory entries and propose promotions to OPENSPACE.md, OPENSPACE.local.md, or retained auto-memory topics; detect duplicates, stale facts, conflicts, and ambiguous entries before making changes.

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。

Performs comprehensive C/C++ security review for memory corruption, integer overflows, race conditions, and platform-specific vulnerabilities. Use when auditing native C/C++ applications, reviewing daemons or services for memory safety, or hunting integer overflow / use-after-free / race conditions in userspace 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。

Deep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI namespace attacks through --extra-index-url resolution ordering, NuGet feed priority exploitation when multiple package sources are configured without clear directives, Maven and Gradle repository ordering where artifact resolution traverses repositories sequentially, Go module proxy abuse through GOPROXY misconfiguration, Ruby gems namespace squatting, and Docker image tag confusion with unqualified image references. Provides complete proof-of-concept methodology using safe callbacks including DNS canary via interactsh or Burp Collaborator and HTTP beacon with no destructive payload. Covers reconnaissance techniques for discovering internal package names through GitHub repository analysis, error message harvesting, JavaScript source map extraction, lock file parsing, job postings mentioning internal tools, and package manifest inspection. Directly references and builds upon Alex Birsan's seminal 2021 dependency confusion research. Each ecosystem section includes registry-specific exploitation mechanics, configuration vulnerabilities, and defensive countermeasures for engagement 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。

Business logic vulnerability testing for web/mobile/API engagements. Covers workflow bypass, state machine violations, multi-step process abuse, price/quantity/discount manipulation, currency confusion, coupon stacking, refund/chargeback abuse, race conditions on logic boundaries, parameter tampering for hidden flows, role/tenant boundary violations, time-of-check vs use, anti-automation defeat, fraud-detection evasion, and subscription/quota abuse. Use when scoping an application after surface-level OWASP Top 10 has been covered, or when the asset is a transactional/marketplace/fintech/e-commerce/SaaS app where logic flaws produce direct financial impact.

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。

Submit compact RNAcentral API requests for RNA entry browsing, single-entry lookup, and cross-reference retrieval. Use when a user wants concise RNAcentral summaries

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。

Capture and interpret iOS Simulator ETTrace profiles. Use when profiling launch or runtime latency, comparing traces, or finding CPU-heavy stacks.

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 any visual design using Adobe Express templates — flyers, posters, social media posts (Instagram, Facebook, LinkedIn), business cards, invitations, greeting cards, resumes, cover letters, brochures, newsletters, certificates, presentations, YouTube thumbnails, email headers, logos, menus, and labels. Use this skill whenever the user wants to make, design, or build any visual — even if they just say "make me a flyer", "design a poster", "I need something for Instagram", "create an event invite", or "make a business card". Also handles browsing templates, editing text, replacing images, changing backgrounds, animating, and exporting designs. Access: 🔐 Signed-In required | Gen AI: ❌ by default — image replacement only where the surface permits generative AI (e.g. Codex); none on Claude

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。