「dependency」の検索結果

Guide for upgrading Grails applications from Grails 7.x to Grails 8, covering Java 21, Groovy 5 name resolution and static compilation, Spring Boot 4.1, Spring Framework 7, dependency management, Micronaut, Jackson 3, Hibernate 7, TagLibs, testing, content negotiation, asset pipeline wildcard paths, and validation behavior 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。

Expert guide for Gradle 9 builds in apache/grails-core on the 8.0.x line - multi-project topology, convention plugins, BOM platforms, dependency rules, task configuration hygiene, and repo-specific patterns that override generic Gradle docs

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。

Configure file watching hooks to auto-react to config changes, env file updates, and dependency modifications. Use to set up reactive workflows.

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。

Have a fast, conversational analysis with the AWS DevOps Agent. Use for cost optimization, architecture review, topology mapping, knowledge / runbook discovery, security audits, dependency questions, and quick diagnostics — anything that needs a 5-30 second answer rather than a 5-8 minute deep investigation. Trigger words include cost, optimize, review, architecture, topology, what runbooks, show me, compare, audit, what if.

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。

Diagnoses and root-causes Amazon MWAA workflow failures across Provisioned (Python DAG) and Serverless (YAML workflow) environments. Provisioned uses aws mwaa invoke-rest-api, CloudWatch log groups, and get-environment; Serverless uses aws mwaa-serverless API (GetWorkflowRun, ListWorkflowRuns, GetTaskInstance) and CloudWatch logs. Covers failed runs and tasks, DAGs not appearing, import errors, worker OOM, IAM denials, and dependency drift. Triggers on: DAG failed, task failed, workflow run failed, MWAA error, debug my DAG, why did my workflow fail, DAG not showing up, MWAA import error, requirements failing, worker crashed, serverless run failed. Not applicable to authoring workflows (handled by authoring-mwaa-workflow), running or smoke-testing a workflow (handled by testing-mwaa-workflow), or CI-CD deploy 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。

Apply codexhost package and native ownership rules when changing production code or dependency directions. Inspect public contracts and run the existing boundary check; skip documentation-only work.

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。

Guidelines for upgrading Expo SDK versions and fixing dependency 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。

Analyze and execute a multi-workload migration into or across Adobe services with contract evidence, dependency waves, dual-run reconciliation, cost controls, and rollback. Use when the task requires adobe platform migration program. Trigger with "Adobe migration plan", "move workflow to Adobe", or "Adobe platform consolidation".

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。

Org-grade attack-surface mapping: given a company's legal identity, discover its ENTIRE owned internet footprint — corporate family -> owned domains -> owned netblocks/ASN -> live assets — with attribution discipline, not just DNS breadth. The org-first attribution pyramid (legal entity -> LEI/registration -> corporate family -> owned domains -> owned netblocks/ASN -> live assets). Corporate-identity resolution via the GLEIF LEI API (legal name -> LEI, exact-LEI direct-children expansion, downward-only depth-capped BFS, NEVER a name re-resolution), SEC-EDGAR full-text search + Exhibit-21 subsidiary entity names, OpenCorporates entity corroboration, Wikidata SPARQL corporate graph (P856/P355/P749/P1830). Domain attribution via reverse-WHOIS (WhoisXML preview-then-purchase quota guard, SecurityTrails associated-domains — both paid), crt.sh O= certificate-transparency organization pivot (keyless), infrastructure correlation (shared NS/MX/SaaS-TXT, netblock membership, reverse-DNS PTR), and the independent-evidence combiner (1-prod(1-w_i), rule of three, OwnerTier NONE/WEAK/MODERATE/STRONG/CONFIRMED) — discover-only `related:` candidates are NEVER auto-scanned. Netblock/ASN attribution via org-first RIR queries (ARIN Whois-RWS org-handle search, RIPE DB organisation + inverse-org search) that recover 'dark netblocks' with no DNS link to the seed, ASN discovery (RIPEstat + BGPView union), the HYPERSCALER-SCOPE GUARD (never attribute a whole AWS/GCP/Azure/Cloudflare announced range to a tenant — keep only the seed-containing block, tag shared_hosting_cdn), and org-identity-seeded internet-scan-index queries (Shodan/Censys/ZoomEye/FOFA/BinaryEdge org: filters + an always-on keyless crt.sh fallback). Promote-to-scan triage ranks forgotten discover-only netblocks by remote-access exposure (gateway-vendor/KEV/control-plane/datastore port scoring) into an operator queue. Attribution confidence rubric + anti-patterns (namesake grafting via GLEIF name re-resolution, single-signal ownership, hyperscaler over-attribution, privacy-WHOIS pivot poisoning, RIR org-name collisions). Passive/keyless-first OSINT only — every paid-key dependency is enrichment on top of a keyless core, never a hard requirement. Use when mapping an organization's full corporate-family internet footprint, resolving a legal entity to its LEI/subsidiaries, discovering domains/netblocks/ASNs an org owns beyond its one seed domain, auditing M&A/shadow-IT sprawl, or scoping an engagement that starts from a company NAME rather than a domain.

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。

Application security covering input validation, auth, headers, secrets management, and dependency auditing

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。

Organize business and technology teams for fast flow using Skelton & Pais's "Team Topologies". Use when the user mentions "team topologies", "Conway's law", "platform team", "stream-aligned team", "team boundaries", "cognitive load", "how should we split teams", "who owns this service", "team dependencies", or "reorg". Also trigger when reorganizing engineering teams, aligning team and service boundaries, splitting a monolith and deciding ownership, reducing cross-team handoffs, or designing an internal platform. Covers the four team types, three interaction modes, the inverse Conway maneuver, and fracture planes. For bounded contexts, see domain-driven-design. For dependency direction in code, see clean-architecture.

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。

Write readable, maintainable code through disciplined naming, small functions, and clean error handling. Use when the user mentions "clean up this code", "this function is too long", "code smells", "naming conventions", "boy scout rule", "single responsibility", or "unit test quality". Also trigger when reviewing a pull request for readability, untangling a messy function, debating comment styles, or improving error-handling patterns. Covers SRP, comment discipline, formatting, and unit testing. For refactoring techniques, see refactoring-patterns. For architecture and dependency rules, see clean-architecture.

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 a source-linked briefing for the latest published GitHub release of a public repository. Use for engineering teams tracking a dependency release; do not use it to publish releases or change repositories.

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。

Wire a scaffolded PortalJS portal to a CKAN backend over its API. Generates a tiny server-side fetch client (no runtime dependency) and feeds the /search catalog and /@namespace/slug showcases from CKAN instead of datasets.json. Use when connecting an existing portal to a live CKAN instance instead of a static manifest.

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 MCP servers using the Leanmcp SDK with decorator-based TypeScript. Use this skill when users ask for "leanmcp", "MCP with decorators", "MCP with authentication", "MCP with elicitation", "MCP with environment injection", or want a simpler, more elegant way to build MCP servers. Leanmcp provides automatic schema generation, dependency injection, authentication, and user input collection.

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。

Manages delivery risk and cross-team dependencies — identifying, sizing, mitigating and escalating what could stop the work. Use this to build a risk register that gets used, manage dependencies between teams, decide what to escalate and when, or work out why the same risks keep materializing unmanaged.

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 and interrogates a project schedule — logic-driven sequencing, dependency types and lags, float and the critical path, resource loading and leveling, schedule risk analysis, and measuring progress against a baseline rather than against optimism. Use this to construct a schedule, audit one you have inherited, find out why a plan keeps slipping, work out what a date change actually costs, or judge whether a reported percentage complete means anything.

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。

Covers what the organization owns and what it is only borrowing — trademarks and clearance, copyright and work-for-hire, patents and trade secrets, open-source license obligations and copyleft reach, and IP terms in customer, contractor and AI-tool agreements. Use this to check whether a name is usable, establish that you own work you paid for, decide how to handle a license obligation in a dependency, or respond to an infringement claim.

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。

基于协议的依赖注入（Protocol-based Dependency Injection），通过精简的协议和 Swift 测试框架（Swift Testing）来模拟文件系统、网络和外部 API，编写可测试的 Swift 代码。

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。

Converts an audited medical research gap into a complete, structured, gap-traceable study design. Always use this skill whenever a user already has one or more candidate research gaps and wants to transform them into an executable biomedical research plan rather than re-run broad topic ideation. Covers six gap-to-design patterns (evidence-completion, mechanism-resolution, cell-state/context-mapping, translation-bridge, causality-upgrade, population/stage-specific) and always outputs one recommended primary protocol, a gap-to-design dependency map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and verified design-support literature rules. Never fabricate references. Preserve claim-evidence discipline and do not replace a topic-specific gap with a generic workflow.

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。

Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk review.

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。

Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk review.

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。

Designs a realistic, execution-aware biomedical study version under explicit constraints of samples, time, budget, data access, lab capacity, team skill, and validation resources. Always use this skill when the user has a real study idea, a candidate route, or a partially framed project but cannot assume ideal conditions. If critical feasibility inputs are missing, first clarify what resources are currently available, what resources may be obtainable, and what resources are realistically unavailable. Do not invent access, capabilities, collaborations, or validation resources. Focus first on feasibility-constrained study framing, route narrowing, dependency control, and minimum viable study design.

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。

Convert technical plans into actionable development tasks with dependency graphs, effort estimates, and parallelization opportunities.

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。