「tokens」の検索結果

Configures CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeConnections, and CodeArtifact. Covers CodePipeline V2 (triggers, variables, execution modes, cross-account), buildspec.yml (caching, VPC, Docker), CodeDeploy strategies (blue/green, canary, linear), CodeArtifact (private package registries, auth tokens, cross-account), and source connections (GitHub, GitLab, Bitbucket). Applies when CodePipeline, CodeBuild, CodeDeploy, CodeConnections, CodeArtifact, buildspec.yml, appspec.yml, or CI/CD pipeline orchestration is referenced. Does NOT cover: ECS Fargate services or task definitions (use aws-containers), CDK Pipelines or cdk deploy (use aws-cdk), sam deploy (use aws-serverless), Amplify deployments (use aws-amplify), or GitHub Actions/GitLab CI.

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Build a typed Attio REST client with tenant-aware tokens, endpoint-specific pagination, structured errors, bounded retries, and contract tests while distinguishing it from the Attio App SDK. Use when creating or refactoring Attio integration code. Trigger with "Attio SDK", "Attio client wrapper", or "typed Attio API".

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 wallet security by analyzing token approvals, permissions, and transaction patterns. Use when checking wallet security, reviewing approvals, or assessing risk exposure. Trigger with phrases like "audit wallet", "check approvals", "security scan", or "revoke tokens".

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 and operate an AssemblyAI Streaming v3 session with safe tokens, audio framing, turn handling, and explicit termination. Use when building live captions or voice agents. Trigger with "AssemblyAI streaming", "AssemblyAI v3 WebSocket", or "live transcript".

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。

Install and configure Apify SDK, CLI, and API client authentication. Use when setting up a new Apify project, configuring API tokens, or initializing apify-client / Apify SDK in your codebase. Trigger with "install apify", "setup apify", "apify auth", "configure apify token".

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 and harden Anima and Figma tokens for design-to-code pipelines. Use when protecting API credentials, restricting Figma access scope, or hardening CI/CD design automation pipelines. Trigger with: "anima security", "anima token safety", "figma token 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。

Organization-grade cloud and supply-chain attack-surface discovery: S3/GCS/Azure Blob bucket discovery via observed-name mining (CNAME/cert-SAN/Wayback) and bounded two-class permutation (6 prefixes x 15 suffixes on trusted tokens, bounded target-bound expansion on subdomain stems), existence (HEAD/GET) vs public-listing confirmation, object-key triage into 9 value tiers (database dumps, credentials, IaC state, kubeconfig, VCS dirs, config, archives, PII, logs), dangling-CNAME bucket-takeover detection, and the ownership-gated severity model that stops an unattributable public bucket from becoming a false CRITICAL; the fully offline AWS-account-ID recovery from a leaked AKIA/ASIA/AROA access key (base32 decode, runnable stdlib Python, canonical test vector, AWS-documentation-example-ID screening); dependency-confusion confirmation for npm/PyPI (internal-signal classifier -- private-registry binding vs org-namespace match -- paired with a read-only public-registry 404 check and the npm scope-claimability nuance the public search API misses); and passive cloud-native/container/Kubernetes/CI control-plane fingerprinting (Lambda URLs, API Gateway, Cloud Run, App Service, kubelet/etcd/K8s API/dashboard, Jenkins/GitLab/Argo CD) as an org-attribution and exposure surface. Passive/discovery only -- no exploitation, no credential submission, no active control-plane confirmation (a stage-6 validate_cloud active tier is described but out of scope). Use when enumerating a target's cloud storage footprint, recovering an AWS account ID from a leaked key, confirming a supply-chain dependency-confusion vector, or fingerprinting cloud-native/K8s/CI infrastructure for an authorized external recon engagement.

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 skillshare on a real Windows guest running in local UTM: build a pinned commit in the devcontainer, push it into the VM, and either run the Windows E2E runbook with full and basic-user tokens or hand the maintainer a one-line hands-on setup. Use this whenever a change touches Windows links, junctions, file symlinks, Developer Mode, copy fallback, Windows paths, or the dashboard on Windows, or when the user asks to test or accept something on Windows / UTM.

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Author SVG figures for Grida docs — diff-able, version-controlled vector diagrams embedded in doc pages instead of screenshots. Provides reusable primitives (selection chrome, size badges, anchor pins, resize cursors, click ripples), color/typography tokens, a starter template, and finished examples to crib from. Canvas user docs (docs/editor/) are the first consumer; the kit is meant to generalize to any product's docs. Use when drawing diagrams that explain UI behaviour — gestures, alignment, before/after states — that a screenshot alone can't capture. Trigger phrases: "svg diagram", "draw a figure", "visual for docs", "explain this gesture visually", "before/after diagram".

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。

Work on Grida's Gateway product consumer, scoped native AI tokens, installed gg provider and Desktop integration. Use for product execution adapters, not standalone Gateway service implementation or billing policy.

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 working with *.excalidraw or *.excalidraw.json files, user mentions diagrams/flowcharts, or requests architecture visualization - delegates all Excalidraw operations to subagents to prevent context exhaustion from verbose JSON (single files: 4k-22k tokens, can exceed read limits)

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。

Dangling markup injection playbook. Use when HTML injection is possible but JavaScript execution is blocked (CSP, sanitizer strips event handlers, WAF blocks script tags) — exfiltrate CSRF tokens, session data, and page content by injecting unclosed HTML tags that capture subsequent page content.

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。

API authentication and JWT abuse playbook. Use when testing bearer tokens, API keys, claim trust, header spoofing, rate limits, and API auth boundary weaknesses.

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 and fix visual hierarchy, spacing, color, and depth in web UIs. Use when the user mentions "my UI looks off" (or amateur/unprofessional), "fix the design", "Tailwind styling", "color palette", "visual hierarchy", "design system", "spacing scale", or "component styling". Also trigger when building consistent design tokens, creating dark mode themes, improving data-visualization clarity, or polishing UI details before launch. Covers grayscale-first workflow, constrained design scales, shadows, and component styling. For typeface selection, see web-typography. For usability audits, see ux-heuristics.

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。

Scaffold a new PortalJS data portal from a brief. Copies the canonical template from examples/portaljs-catalog and substitutes project tokens. Use when starting a brand-new data portal project from scratch.

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 building UIs leveraging the WordPress Design System (WPDS) and its components, tokens, patterns, etc.

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。

Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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Builds and maintains the design system a product is assembled from — tokens for color, type, spacing and elevation, component contracts, and the rules that keep them coherent as the product grows. Use this when starting a new interface, when screens have drifted apart visually, when the same component exists three times in slightly different forms, or when a token or component needs adding without breaking what exists.

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。

Context window monitoring and budget management. Keeps orchestrator at 15-30% context usage while subagents get full 200k tokens. Provides warnings at thresholds, context-aware summarization triggers, and wave-level budget planning.

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。

Replay an LLM inference request trace (Mooncake / vLLM / SGLang hash_ids format) against a block-level KV prefix cache and compute hit statistics. Use when given a request trace plus cache configuration and asked for hit rate, hit tokens, or final cache contents. Covers the longest-contiguous-prefix semantics that distinguishes KV prefix caching from full-prompt prompt caching, the policy-specific residency and eviction rules (LRU, LFU, S3FIFO), and the partial-last-block accounting rule.

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 interface designs, wireframes, and design systems. Masters user research, accessibility standards, and modern design tools. Specializes in design tokens, component libraries, and inclusive design. Use PROACTIVELY for design systems, user flows, or interface 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。

Build scalable design systems with Tailwind CSS, design tokens, component libraries, and responsive patterns. Use when creating component libraries, implementing design systems, or standardizing UI patterns.

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Generate a complete, accessible brand design system from a brief — primitive → semantic → component DTCG tokens (color, type, spacing, radius, shadow, motion), light + dark, plus a single theme.css — verified for WCAG. Use when the user wants a from-scratch brand/design foundation, a new palette + type system, or a themeable token kit for a product.

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 dense, data-heavy screen - an analytics console or a trading terminal - with real charts drawn from tokens: candlestick, volume, depth, stacked area, waterfall, scatter, correlation matrix, donut, gauge, sparklines, heatmaps and order books. Use when the request is a dashboard, terminal, monitoring view, data console, or any screen whose job is to show many numbers at once. Covers the layout sequence, the SVG geometry, the accessibility contract per chart type, and the contrast traps that only appear in dark mode.

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。