「pipeline」の検索結果

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.

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Use this skill when defining AI governance policies, designing human oversight workflows, documenting bias mitigation strategies, or meeting regulatory transparency requirements for Salesforce AI features. Trigger keywords: responsible AI, AI bias, AI audit trail, AI transparency, human-in-the-loop, AI risk inventory, AI disclosure. NOT for the MLOps pipeline or Policy-as-Code engine architecture — use architect/ai-governance-architecture. NOT for Trust Layer technical configuration — use agentforce/einstein-trust-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。

GitHub Actions workflow patterns for React Native iOS simulator and Android emulator cloud builds with downloadable artifacts. Use when setting up CI build pipelines or downloading GitHub Actions artifacts via gh CLI and GitHub 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。

B2B sales pro AI — SPIN, MEDDIC, BANT, cold outreach, objection handling, pipeline

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。

ML Engineer — model deployment, MLOps pipeline, feature store, model monitoring, A/B testing, production ML system 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。

Fully autonomous bug hunting pipeline — discover bugs in a scoped area using parallel subagents, independently triage each finding, fix confirmed issues with subagents, then audit all fixes against repo constraints and target platforms. Runs end-to-end without user interaction.

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。

Orchestrate AI coding agents (Claude Code, Codex, OpenCode) in isolated sandboxes using the @ai-hero/sandcastle SDK. Use when the user needs to (1) run agents AFK in Docker/Podman containers, (2) build multi-agent pipelines with plan-execute-review patterns, (3) run parallel agents on separate worktrees, (4) create iterative agent loops with maxIterations, (5) extract structured output from agent runs, (6) set up sandcastle in a new or existing project, or (7) write prompt files with template args and shell expressions.

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。

Assemble a finished piece from human-written fragments via an orchestrated two-loop pipeline - an assembly loop (assembler + cold reviewer) that sequences the fragments into a draft, then a polish loop (polisher + cold reviewer), then frequency analysis and a catalog-deslop pass with a regression gate. Two modes with opposite fidelity contracts - stitch mode preserves the author's exact wording, narrative mode preserves every idea but may rewrite freely. Use when the user says "mosaic", "assemble my fragments", "stitch these notes into a post", or provides a fragments file to turn into a finished piece. For writing from a topic with research, use article-factory; for prose from scratch, use the prose skill.

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 or audit the approved Quiet Signal core visual language when the user explicitly asks for Quiet Signal styling on a defined website, interface, poster, social graphic, report, presentation, or other design artifact. This skill supplies visual identity and rule checks; it does not plan content, invent platform requirements, or run a production pipeline.

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。

Stand up reporting for a new audience — an external client, a business unit, a region, an executive team — end to end: what they need to see, whether the data exists, access and scoping, their place in the pipeline, the standard report set, and validation against numbers they can check themselves. Use when a new audience is onboarded, when an existing one adds a site, a region or a business unit, when their reporting is rebuilt after a change on their side, or when they say the numbers do not match their own records.

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。

Outbound SDR (Sales Development Representative) operating system that runs the full top-of-funnel motion across HubSpot (CRM, engagement, and source of truth) and Exa (web research + signals). Use this skill WHENEVER the user is doing outbound sales development, building target/prospect lists, defining or refining an ICP, enriching leads, researching accounts or people before outreach, writing cold emails or multi-touch sequences, qualifying or scoring leads, logging activity to CRM, handing meetings off to AEs, or reporting on pipeline. Trigger it even when the user only says things like "find me 50 leads", "research this account", "write a cold email to this person", "score these leads", "log this in HubSpot", or "build a sequence"; these are all SDR tasks this skill governs. Do not wait for the user to say "SDR" or "prospecting" explicitly.

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。

Understand what SKMTC is, how its engine works, and the architectural invariants — for agents building or extending infrastructure *around* SKMTC rather than authoring generators or running the CLI. Covers the three-phase pipeline, the host/Worker boundary, cross-generator coordination, the manifest, the attribution / gen-maps (provenance) subsystem, the package graph, the dependency substrate, and the design decisions that make SKMTC behave unlike a typical codegen tool. Use this skill when the user asks "what is SKMTC", "how does the SKMTC engine work", "explain the SKMTC architecture", or is building platform infrastructure around SKMTC — a hosted generate API, a schema or generator registry, tracing or provenance tooling, a web app or SaaS that wraps the engine, or platform-level CI integration. This skill is the system mental model. It does NOT cover authoring generators (→ skmtc-generator), running CLI commands (→ skmtc-cli), or diagnosing broken runs (→ skmtc-debug).

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。

The GraphQL pipeline for SKMTC generators — authoring generators whose input schema is GraphQL SDL rather than OpenAPI. Covers `toGqlOperationEntry`, `GqlOperation`, `synthesizeArgsObject` (mutation args -> object schema), the GQL enrichment routing (`[id][rootKind][fieldName][variant]` — two nested subject keys where OAS has path+method), the `to<Lang>GqlOperationProjectionBase` companion factories, and the `GeneratorKey` shape `id|rootKind|fieldName|variant`. Use this skill ALONGSIDE `skmtc-generator` whenever the schema source is GraphQL SDL or the task mentions "GraphQL", "SDL", "GqlOperation", "toGqlOperationEntry", or GraphQL query/mutation generators. Engine rules (producers, register/insert, the axioms) stay in `skmtc-generator`; this skill carries only what differs for GraphQL.

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。

Game art principles. Visual style selection, asset pipeline, animation 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。

Use this skill when the user is working with an Aspire distributed application and needs to operate the AppHost or its resources through the Aspire CLI: start, restart, stop, or wait on the app; inspect resources, logs, traces, docs, or health; add integrations; manage secrets or config; publish, deploy, or rerun a named pipeline step; initialize Aspire in an existing app; recover missing `.modules` files in a TypeScript AppHost; discover the right frontend URL for Playwright from Aspire state; expose custom dashboard/resource commands; or understand unfamiliar Aspire AppHost APIs in C# or TypeScript. Use it even if they describe the task in terms of an AppHost, resources, dashboard, existing app bootstrap, missing generated modules, Playwright URL discovery, C# API understanding, or local distributed app workflow without explicitly naming Aspire. Do not use it for non-Aspire .NET apps, container-only repos with no AppHost, or ordinary build and test 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。

Autonomous comprehensive refactoring. Three-phase pipeline — Phase 1 /refactor (tactical, loops internally to convergence) → Phase 2 loop of /review-arch + /implement-batch until architectural findings converge below a severity floor (default HIGH+) → Phase 3 /refactor (catches tactical issues introduced by restructuring). Auto-approves /review-arch ticket proposals; pulls the andon cord on contested findings, breaking-change proposals, repeated implementation failure, or Phase-2 hard-cap exhaustion (5 architectural iterations).

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。

Full-lifecycle project workflow. Takes batched tickets, implements via /implement-batch, runs smoke tests, then executes a comprehensive quality pipeline (refactor, review-arch, review-test, tidy-docs, review-release). Maximizes autonomy with andon cord escape.

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。

Autonomous comprehensive review. Once-through pipeline over /review-health, /review-arch, /review-security, /review-perf, /review-a11y, /review-test, /review-release. Operator-configurable ticket creation at startup — when ON, auto-approves sub-skill ticket proposals per the orchestrator-family contract; when OFF, uniformly declines and surfaces findings in the consolidated report. Auto-detects sub-skills that do not apply (no web content → skip /review-a11y; no tests → skip /review-test).

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。

Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications.

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。

Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.

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。

Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.

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。

Design and build cohesive web pages with custom visual identity — landing pages and portfolios get rich anatomy + section archetypes; any other page type (blog, about, pricing, contact, coming-soon, dashboard, admin, e-commerce, custom) is supported through generic anatomy + skeleton. Use this skill whenever the user mentions: landing page, portfolio, personal site, hero section, marketing page, product page, sales page, splash page, blog page, about page, pricing page, contact page, coming-soon, waitlist, dashboard, admin panel, e-commerce store, redesign my site, design my portfolio, build a portfolio, work showcase, hire-me page, perfect-ui, perfect landing, or asks to create any web page surface. Two tiers: special (landing | portfolio — rich treatment) and generic (everything else — universal craft toolkit). Self-contained 8-phase pipeline: vibe discovery → visual direction (color/typography/mood) → custom icon set (NO emoji, NO icon library) → AI-generated visuals → optional shader effects layer → inline plan + implement on Next.js + Tailwind + shadcn. Always proposes effect layer as optional. No refusals; outputs distinctive sites, not AI slop.

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 any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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。

Multi-cycle diagnostic pipeline: profile → research → optimize → repeat with full-stack bottleneck 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。