「branching」の検索結果

Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Focuses on recently modified code unless instructed otherwise. This skill should be used when code-quality checks pass but the code would benefit from structural cleanup — deduplication, branching simplification, naming improvements, or dead-code removal. Invoked as a subagent from /code-quality or directly via the Task tool.

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Create a well-structured GitHub PR with proper branching, testing, formatting, and documentation. Use when the user says "create a PR", "make a PR", "open a pull request", or wants to submit changes for review. Handles the full workflow: branch creation, implementation, testing, formatting, committing, and PR creation with comprehensive descriptions.

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 designing lead nurture journeys in MCAE (Account Engagement / Pardot) Engagement Studio — mapping content to funnel stages (Awareness, Consideration, Decision), behavioral trigger rules, branching program paths, and MQL handoff criteria to Sales. NOT for building a journey in Marketing Cloud Journey Builder — use admin/journey-builder-administration. NOT for the scoring and grading model behind MQL — use admin/mcae-lead-scoring-and-grading.

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Specify a FlexCard before a developer opens Card Designer: the card-state set and the condition that selects each state, the data source type behind each card (DataRaptor, Integration Procedure, Apex remote, SOQL), the action menu users get (navigate, launch OmniScript, Apex, DataRaptor), and every embedded child FlexCard or custom LWC. Produces the artifacts a BA hands to the builder. Trigger keywords: FlexCard requirements, FlexCard BA, FlexCard layout design, FlexCard data sources, FlexCard actions, FlexCard card states, OmniStudio FlexCard scoping. NOT for building the card in Card Designer, NOT for OmniScript step and branching requirements (use admin/omniscript-flow-design-requirements), NOT for standard Lightning record-page component requirements.

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 designing the FSC client onboarding process — mapping document collection touchpoints, approval steps, compliance checkpoint sequencing, and welcome journey handoffs. Trigger keywords: client onboarding design, onboarding workflow requirements, document collection flow, compliance checkpoint, welcome journey, intake process design. NOT for configuring the Action Plan template itself — use admin/fsc-action-plans. NOT for OmniScript screen and branching requirements — use admin/omniscript-flow-design-requirements.

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Router for the 70 SfSkills `devops` skill packages. Salesforce delivery: source tracking, packaging, branching, CI/CD pipelines, environment strategy and deployment troubleshooting. Use when the request mentions deploy, deployment, sfdx, sf CLI, scratch org, sandbox, unlocked package, change set, CI/CD, GitHub Actions, release, rollback, source tracking. Finds and opens the exact skill package to read; it does not contain the guidance itself.

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。

GitHub patterns using gh CLI for pull requests, stacked PRs, code review, branching strategies, and repository automation. Use when working with GitHub PRs, merging strategies, or repository management 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。

Git expert covering branching strategies, collaboration, conflict resolution, and best practices

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 adaptive learning and student personalization systems for pedagogical quality. Triggers: you need to evaluate learning path algorithms (branching, remediation, acceleration).

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 game narrative systems for technical quality -- branching dialogue trees, state/flag tracking, quest systems, choice-consequence mapping, localization pipelines, voice-over integration, and cinematic scripting..

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。

Squad branching model: dev-first workflow with insiders preview channel

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。

ออกแบบเรื่องในเกม — lore, branching dialogue, character arc, quest design, environmental storytelling

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。

Git workflow patterns including branching strategies, commit conventions, merge vs rebase, conflict resolution, and collaborative development best practices for teams of all sizes.

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。

Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, or when you need to organize work across multiple parallel streams.

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。

Structures git branches and worktrees: keeps unrelated changes on separate branches, isolates each in its own worktree created so the repository's setup runs, records dependencies with git-machete, and recombines them into a temporary mixdown branch for local testing. Use before creating any branch or worktree in a codebase that works on more than one branch, including branching off the default branch to start a change; when starting work in a fork, clone, or third-party checkout; when choosing what a new branch should be based on; when a branch is growing a second unrelated concern; when deciding whether to stack branches or keep them independent; when preparing a change for a pull request or patch submission; when handed an existing worktree or branch to implement and commit in a fork; or when a local build needs several in-progress branches combined. Not needed where the repository clearly commits everything to the trunk, or holds notes or personal data rather than 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。

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

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 cognitive task analysis to expert work that depends on perceptual cues, branching judgment, and recurring monitoring loops. Use when decomposing expert capability into agent structure, simulation design, or validation interviews. NOT for ordinary step-by-step SOP capture or simple pipelines with no tacit cue layer.

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。

Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, or when you need to organize work across multiple parallel streams.

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。

Walk every branching path and boundary condition in content, report only unhandled edge cases. Orthogonal to adversarial review - method-driven not attitude-driven. Use when you need exhaustive edge-case analysis of code, specs, or diffs.

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 a B2B cold-outbound sequence", "design reply-triage branching", "plan a domain warmup / sending throttle", or "make my outbound CAN-SPAM / opt-in compliant"; produces a multi-step outbound sequence with reply-triage branches (positive / objection / referral / not-now / opt-out), a warmup + send-throttle ramp schedule, jurisdiction opt-in/CAN-SPAM guardrails (guidance, not legal advice), and a SEND S-dimension read. Not for B2C lifecycle flows — use email-sequence-designer; not for the consent record — use consent-registry; not for computing EQS — use email-quality-auditor. B2B冷启动外联序列/回复分流/域名预热

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。

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

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。

Git workflows, branching strategies, collaboration, and code 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。

Neon is a serverless Postgres platform that separates compute and storage to offer autoscaling, branching, instant restore, and scale-to-zero. It's fully compatible with Postgres and works with any language, framework, or ORM that supports Postgres.

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 patterns for Neon serverless Postgres, branching, connection pooling, and Prisma/Drizzle 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。