「data write」の検索結果

Run a dogfooding session for hyalo — build from source, exercise the CLI against real knowledgebases (own KB, MDN, GitHub Docs, VS Code docs), find bugs, verify recent fixes, assess UX, measure performance, and write a structured report. Use this skill whenever the user says /dogfood, "dogfood", "run a dogfood session", "test hyalo against real data", or wants to exercise hyalo on real knowledgebases to find issues.

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 should be used when the user asks to "generate tasks", "create implementation plan", "break down feature", "write agent prompts", "decompose into tasks", "create work items", or when creating agent-ready task descriptions from PRD and SDD documents.

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 well-structured prompts for AI agents using proven architecture patterns. Use when users ask to write agent prompts, system prompts, or agent instructions, or want to improve existing prompts that aren't working.

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 should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Gemini CLI plugins.

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 should be used when the user asks to 'create an agent', 'add an agent', 'write a subagent', 'agent frontmatter', 'when to use description', 'agent examples', 'agent tools', 'agent colors', 'autonomous agent', or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

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 should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

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 should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

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 production-ready business documents including freelance contracts, project proposals, SOWs, NDAs, and MSAs with jurisdiction-aware clauses. Covers US (Delaware), EU (GDPR), UK, and DACH (German law) legal frameworks. Includes contract templates, clause libraries, and DOCX conversion. Use when starting client engagements, writing proposals, drafting partnership agreements, or needing GDPR-compliant data processing addenda.

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 comprehensive integration tests for component interactions, workflows, and system boundaries. Use for testing API endpoints, database operations, and multi-component flows.

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。

Stack-specific security implementation guidance (backend, frontend, database, infrastructure, operations) with auto-detection from your changes. Use when implementing a feature securely or hardening code as you write it. Trigger on "how do I secure this", "security best practices", "is this secure", "harden this". For scanning existing code use /security-verify.

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。

DOM-based XSS occurs when JavaScript reads attacker-controlled sources (`location.hash`, `document.referrer`, `window.name`, `location.search`) and passes them to dangerous sinks (`document.write`, `innerHTML`, `eval`, `location.href`, `setTimeout`, `jQuery.html()`) without sanitization. Unlike reflected/stored XSS, payloads never reach the server. Detect by auditing JavaScript for tainted data flow from DOM sources to sinks. Tools: Burp Suite DOM Invader, Chrome DevTools, DOMPurify (fix).

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。

WatermelonDB reactive local database for React Native - schema, models, decorators, reactive queries, relations, writers/readers, batch operations, migrations, sync

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。

Frames a structured, testable threat-hunting hypothesis: grounding it in adversary behavior and available telemetry, defining the data sources and detection logic, and setting success criteria and outcomes. Activates for requests to start a threat hunt, write a hunt hypothesis, or plan a hypothesis-driven hunt.

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 fantasy character names in zh-TW with original spelling and etymology, across human, elf, dwarf, orc/beastfolk, and halfling naming traditions. Use when the user needs a name for a character, NPC, party member, villain, shopkeeper, or monster, asks to think of, suggest, or rename such a character, names entities for a MUD/TRPG/game world or worldbuilding document, or writes lore, quests, presets, or seed data that require in-world personal names.

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。

Account-based marketing for B2B SaaS. Use this skill to build a target account list, tier it 1:1 / 1:few / 1:many, size it against sales capacity, turn intent and engagement signals into plays, write the multi-channel orchestration contract each tier runs on, and measure the program in account coverage, penetration and pipeline instead of MQLs. Also triggers on: ABM, account-based marketing, target account list, TAL, named accounts, account tiering, 1:1 ABM, one-to-few, programmatic ABM, account selection, ideal customer profile fit, intent data, buying signals, 6sense, Bombora, Demandbase, account penetration, account coverage, sales and marketing alignment on accounts, enterprise account program.

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 a task needs the judgment of a Blockchain Engineer — applying the checks-effects-interactions pattern to prevent a reentrancy exploit, auditing a privileged/administrative function for missing access control, designing a manipulation-resistant oracle for on-chain price data, minimizing gas cost through storage-write design, or deciding whether a smart contract needs an upgradability pattern before 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。

Create, run, and maintain API test collections using Bruno (OpenCollection YAML format and legacy Bru format). Use when the user wants to: (1) create a Bruno API test collection from scratch or from OpenAPI/Swagger specs, (2) write API request files with tests and assertions, (3) run API tests using bru CLI, (4) generate test reports (HTML, JUnit, JSON), (5) set up CI/CD pipelines (GitHub Actions) for automated API testing, (6) debug or fix failing Bruno API tests, (7) add environment configurations for API testing, (8) chain API requests with data extraction, or (9) work with any .yml/.bru Bruno collection files. Triggers on mentions of 'Bruno', 'bru CLI', 'API testing collection', 'OpenCollection', or requests to automate API testing with file-based collections.

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 Python 3.11+ applications requiring type safety, async programming, or robust error handling. Generates type-annotated Python code, configures mypy in strict mode, writes pytest test suites with fixtures and mocking, and validates code with black and ruff. Invoke for type hints, async/await patterns, dataclasses, dependency injection, logging configuration, and structured error handling.

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 designing new high-level system architecture, reviewing existing designs, or making architectural decisions. Invoke to create architecture diagrams, write Architecture Decision Records (ADRs), evaluate technology trade-offs, design component interactions, and plan for scalability. Use for system design, architecture review, microservices structuring, ADR authoring, scalability planning, and infrastructure pattern selection — distinct from code-level design patterns or database-only design 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。

Build custom AI prompts from scratch using guided workflows and patterns from a 2,500+ prompt database. Supports image, video, and text prompts for Midjourney, Flux, Leonardo AI, DALL-E, Sora, and 12 more models. Use when user says "build a prompt", "create a prompt", "write a prompt", "make me a prompt", "new prompt", or "prompt 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。

Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when interacting with gcsfuse: decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and config files, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or fully POSIX-compliant shared file systems (Filestore, Managed Lustre).

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 testing, evaluating, or building regression suites for Agentforce agents: conversation testing in Agent Builder, topic (now subagent) coverage and utterance testing, Testing API and AiEvaluationDefinition metadata, Agentforce DX CLI test runs (sf agent generate test-spec, sf agent test create/run/resume/results/list), evaluation metrics (containment rate, escalation rate, CSAT, topic activation accuracy), and post-deploy analytics via Enhanced Event Logs. Triggers: 'how do I test my Agentforce agent', 'agent routes to wrong subagent', 'write utterance tests', 'regression test after topic change', 'measure agent quality', 'agent containment rate', 'run agent tests from the CLI'. NOT for agent creation, topic design, or action contract design — use agentforce/agentforce-agent-creation, agentforce/agent-topic-design, or agentforce/agent-actions respectively.

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。

Pre-production security checklist for Agentforce deployments: agent run-as permission scope, grounding-source data classification, action write-scope, audit trail. NOT for the full go-live readiness gate covering cost telemetry, rate limits, rollout and rollback — use agentforce/agentforce-production-readiness-checklist. NOT for a general org security review — use security/security-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。

Designing Campaign Hierarchy for program-level ROI tracking, configuring Customizable Campaign Influence (CCI) attribution models, and interpreting multi-touch attribution from MCAE B2B Marketing Analytics. Trigger keywords: campaign ROI, attribution model, campaign hierarchy, first-touch, last-touch, multi-touch, CCI, campaign influence, revenue attribution, campaign member status. NOT for deciding which attribution model and KPIs to adopt before any config - use admin/marketing-reporting-requirements. NOT for MCAE connector setup or the campaign sync that writes Campaign Member records - use admin/mcae-pardot-setup. Also covers: CampaignSettings, enableCampaignInfluence2, enableAutoCampInfluenceDisabled, enableB2bmaCampaignInfluence2, enableAccountsAsCM, CampaignInfluenceModel metadata, isDefaultModel, isModelLocked, recordPreference, AllRecords, RecordsWithAttribution, CampaignInfluence.RevenueShare, ModelType, CampaignMemberStatus IsDefault HasResponded SortOrder, HierarchyActualCost, HierarchyAmountWonOpportunities, TotalNumberofResponses, Opportunity.CampaignId primary campaign source.

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。