「va」の検索結果

Configuring or troubleshooting Salesforce CPQ Advanced Approvals: SBAA__ApprovalRule__c, SBAA__ApprovalVariable__c for cross-line aggregation, SBAA__ApprovalChain__c for ordered approver sequences, escalation timeouts, Smart Approvals for re-quote skip logic, and the managed package's permission sets. Trigger keywords: CPQ Advanced Approvals, SBAA approval rule, approval variable, approval chain, discount approval, line-level approval, Smart Approvals, requote approval. NOT for standard non-CPQ Salesforce approval processes - use admin/approval-processes. NOT for CPQ price rules and discount schedules - use admin/cpq-pricing-rules.

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Read, query, and write WooCommerce product variations correctly — the WC_Product_Variable (parent) vs WC_Product_Variation (child) class split, the parent's get_variation_prices( $for_display ) cached aggregation and how to bust the wc_var_prices_<id> transient, programmatic variation creation via WC_Product_Variation + set_parent_id + set_attributes + save followed by WC_Product_Variable::sync, the inherited-vs-own variation stock model (parent flag, variation flag, derived stock_status), get_available_variations for frontend variation data, and the $for_display tax-handling parameter that breaks display logic when forgotten. Use when scaffolding plugin code that creates / queries / modifies variations or when debugging stale variation data after programmatic writes. Triggers on WC_Product_Variation, WC_Product_Variable, get_variation_prices, get_available_variations, product_variation post type, wc_var_prices, sync_variation, or programmatic variation creation context.

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DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, traced evals, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval; for instrumenting an app with DeepEval tracing, @observe, or framework integrations (use the `deepeval-tracing` skill); or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill).

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Spin up a working LiveAvatar demo from a curated catalog — clones the reference repo, installs dependencies, provisions the LiveAvatar account, and fills the env file, then hands off the parts only a human can do. Use when: (1) User wants to try, test, see, or demo LiveAvatar, (2) User asks what LiveAvatar demos or examples exist, (3) User wants a sales agent / lead-qualification avatar, (4) User wants a LiveKit agent driving a LiveAvatar avatar, (5) User wants an avatar joining their own LiveKit room, (6) User wants a speech-to-speech avatar, a GPT-Live demo, a language-learning or tutor avatar, a customer-support avatar, a poker coach / game-style avatar, or an avatar with on-screen visuals/overlays, (7) User says "run the LiveAvatar demo", "show me LiveAvatar", "get me started with LiveAvatar", or "clone the LiveAvatar example", (8) User is evaluating LiveAvatar and wants something running before writing their own integration.

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Specialized skill for testing FluentValidation validators. Use when you need to create tests for Validator classes, validate business rules, or test error messages. Covers complete FluentValidation.TestHelper usage, ShouldHaveValidationErrorFor, async validation, cross-field logic, etc. Keywords: validator, validation, fluentvalidation, validation testing, UserValidator, CreateOrderValidator, TestHelper, ShouldHaveValidationErrorFor, ShouldNotHaveValidationErrorFor, TestValidate, TestValidateAsync, testing validators, validating business rules

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Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangChain, OpenAI Agents, LlamaIndex, Pydantic AI, CrewAI, and others); choose between a native integration and manual instrumentation; set span types, tags, or metadata; or send DeepEval-SDK traces to Confident AI's Observatory. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill), or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill). This skill is purely DeepEval-SDK instrumentation — producing well-formed traces, not running evals.

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Create a persistent HeyGen avatar — a reusable face + voice identity for the agent, the user, or any named character — powered by HeyGen Avatar V technology. Prompt-based creation by default (description → HeyGen builds it); photo upload is optional for real-person digital twins. Use when: (1) giving the agent a face + voice so it can present videos ("bring yourself to life", "create your avatar", "give yourself an avatar", "design a presenter", "set up an avatar", "let's make an avatar"), (2) the user wants to appear in videos as themselves ("create my avatar", "I want my face in a video", "digital twin of me", "build me an avatar"), (3) building a named character presenter ("create an avatar called Cleo", "design a character named X"), (4) establishing HeyGen identity before making videos — the correct FIRST step when no avatar exists yet. Chain signal: when the user says both an identity/avatar action AND a video action in the same request ("create an avatar AND make a video", "set up identity THEN create a video", "design a presenter AND immediately record"), run heygen-avatar first, then heygen-video. Returns avatar_id + voice_id — pass directly to heygen-video to create HeyGen videos. NOT for: generating videos (use heygen-video), translating videos, or TTS-only tasks.

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Pick the right business-model canvas (Lean Canvas, Business Model Canvas, or Value Proposition Canvas) for the stage and fill it with specifics — one segment, one primary canvas, top-3 assumptions, no fluff in the moat or channel boxes. Load when the user asks to fill a business model canvas, lean canvas, value proposition canvas, model this business, map the business model, says "fill the BMC", "make a Lean Canvas", "Value Proposition Canvas for this", "model this idea", "what's the business model", "design the business model". Sub-skill of `venture-exploration`. Hard-bans "everyone" segments, generic channels ("SEO/social/content/ads"), and "unfair advantage = AI/data/network effects" with no concrete asset. Does NOT score viability — for that use `idea-evaluation`.

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Use when you need to refactor Java code to adopt modern Java features (Java 8+) — including migrating anonymous classes to lambdas, replacing Iterator loops with Stream API, adopting Optional for null safety, switching from legacy Date/Calendar to java.time, using collection factory methods, applying text blocks, var inference, or leveraging Java 25 features like flexible constructor bodies and module import declarations. This should trigger for requests such as Review Java code for modern Java development; Apply best practices for modern Java development in Java code; Modernize Java code with records pattern matching or switch expressions; Replace legacy idioms with modern Java features; Adopt Java 8+ language features safely. Part of Plinth Toolkit

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Design, review, or troubleshoot Salesforce Approval Processes. Triggers: 'submit for approval', 'approver', 'record locked', 'recall approval', 'approval step', 'discount approval', 'approvalProcess metadata', 'ProcessInstanceWorkitem', 'recordEditability', 'process order', 'no approver found', 'pending approval'. NOT for submitting or acting on approvals from Apex - use admin/approval-process-apex-patterns. NOT for CPQ Advanced Approvals (SBAA rules and chains) - use admin/cpq-approval-workflows. NOT for multi-stage cross-object orchestration with SLAs - use flow/orchestration-flows.

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Design automated evaluation pipelines for LLM and agent systems — combining deterministic checks, statistical metrics, and LLM-as-judge scoring into repeatable, CI-integrated eval suites. Load when the user asks to set up automated evals, design an eval pipeline, integrate evals into CI/CD, create an eval suite, do eval-driven development, or says "automate my evals", "CI eval integration", "evaluation pipeline", "continuous evaluation", "monitoring eval quality", "set up regression testing for my agent". Sub-skill of eval-output orchestrator.

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Dung khi designer se lam TREN CANVA hoac Figma va can direction thao tac cu the — chon template base, thu tu thao tac, map tung element vao vi tri, luoi va khoang cach, mau va font lay tu brand kit, checklist export, viec nen va khong nen lam. Kich hoat khi user nhac 'brief Canva', 'huong dan lam tren Canva', 'direction Canva', 'template Canva', 'layout Canva', 'lam trong Figma', 'ban design chua ranh nen phai chi tay'. Khong dung cho — brief concept anh tinh khong gan cong cu thi dung skill 42-brief-hinh-anh; chuoi slide carousel thi dung skill 43-brief-carousel; quy dinh mau, font va logo cua thuong hieu thi dung skill 46-brand-guideline.

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Use when you need to design, review, or improve validation in Spring Boot applications — including Bean Validation on request DTOs, @Valid/@Validated at API boundaries, constraint groups, custom constraints, @ConfigurationProperties validation, nested DTO validation, and consistent validation error handling. This should trigger for requests such as Add validation support in Spring Boot; Review Spring Boot validation rules; Improve request validation in Spring Boot REST APIs; Add custom Bean Validation constraints in Spring Boot; Validate configuration properties in Spring Boot. Part of Plinth Toolkit

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Produce and review production image-generation and image-editing workflows with Amazon Nova Canvas on Amazon Bedrock, including native InvokeModel payloads, safe authentication, validation, retries, cost controls, provenance, and lifecycle migration checks. Use when a task names Nova Canvas, amazon.nova-canvas-v1:0, Bedrock image generation, Canvas inpainting/outpainting/background removal, image conditioning, color guidance, image variation, virtual try-on, or Canvas fine-tuning.

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Operate ArvanCloud (arvancloud.ir) through its REST APIs, including CDN and DNS records, domains, cache purge, WAF and rate limits, Cloud Server (IaaS v3, v1 and the undocumented v2 backups), Object Storage, Edge Computing, Cloud Container, VOD, Live and Video Ads, plus Let's Encrypt DNS-01 certificates via acme.sh dns_arvan. Use when the user wants to list, create, change or delete anything on ArvanCloud, take an account inventory, find out which account a key belongs to, check quota or usage, or debug an ArvanCloud API error. Also trigger on hosts like napi.arvancloud.ir, ecc.{region}.arvanapis.ir, storage.arvanapis.ir, dejban.arvancloud.ir, an "Apikey" Authorization header, the dns_arvan plugin, or one of the user's ArvanCloud-hosted domains.

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"Corporate innovation-governance toolkit integrating Stage-Gate process, 3 Horizons model, innovation portfolio management, open innovation, corporate venture capital (CVC), innovation KPIs, and intrapreneurship. Use for innovation-portfolio design, second-curve planning, innovation-project review gating, open-innovation evaluation, CVC setup, innovation-KPI design, or managing tension between core and new businesses. Triggers: 『第二曲線』『創新專案怎麼管』『新事業孵化』『收購投資新創』『Stage-Gate』『研發投資組合』『內部創業』『開放式創新』『CVC』『3 Horizons』『創新 KPI』. For Taiwan EMBA innovation-management/strategy/technology-management cases (台大／中山). Startup basics: use Asgard `ux-lean-startup`; innovation theory: use Asgard `grad-disruptive-innovation`, `grad-ambidexterity`; 家族二代接班治理: use `biz-corporate-governance` 或 `ops-talent-strategy`; ESG/淨零策略結合: use `biz-net-zero-transition`.".

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Use when creating or managing picklist fields: choosing between Global Value Sets and object-local picklists, configuring controlling and dependent field relationships, managing picklist values, and replacing values in existing data records. NOT for why the API or an integration ignores a dependency matrix - use admin/field-dependency-and-controlling. NOT for cleaning up degraded, unrestricted or orphaned picklist values - use admin/picklist-field-integrity-issues. NOT for record type picklist filtering - use admin/record-types-and-page-layouts. Keywords: GlobalValueSet, StandardValueSet, __gvs suffix, customValue, valueSetName, valueSetDefinition, restricted picklist, GlobalValueSetTranslation, OpportunityStage, CaseStatus.

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Build a LiveAvatar integration end-to-end — assesses the user's existing stack, recommends the optimal path, and guides implementation. Use when: (1) Building a new LiveAvatar integration, (2) Adding a real-time avatar to an app or site, (3) Connecting LiveAvatar to an existing AI pipeline, (4) User mentions LiveAvatar, real-time avatar, interactive avatar, conversational avatar, or lip-sync avatar, (5) Deciding between Embed, FULL Mode, and LITE Mode, (6) Migrating from HeyGen Interactive Avatar to LiveAvatar.

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Build a LiveAvatar integration end-to-end — assesses the user's existing stack, recommends the optimal path, and guides implementation. Use when: (1) Building a new LiveAvatar integration, (2) Adding a real-time avatar to an app or site, (3) Connecting LiveAvatar to an existing AI pipeline, (4) User mentions LiveAvatar, real-time avatar, interactive avatar, conversational avatar, or lip-sync avatar, (5) Deciding between Embed, FULL Mode, and LITE Mode, (6) Migrating from HeyGen Interactive Avatar to LiveAvatar.

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Provides context about the Roo Code evals system structure in this monorepo. Use when tasks mention "evals", "evaluation", "eval runs", "eval exercises", or working with the evals infrastructure. Helps distinguish between the evals execution system (packages/evals, apps/web-evals) and the public website evals display page (apps/web-roo-code/src/app/evals).

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Use when the user asks to "set up conversion values so tROAS optimizes profit not orders", "map margin onto my purchase value", "build value rules for lead / phone / signup conversions", or "stop bidding to revenue when I care about profit"; defines and QAs the conversion VALUE model — per-conversion values, margin/net-value adjustment, static-vs-dynamic value rules, proxy values for non-revenue actions, and a value-vs-count sanity check — as a value-model spec plus a pre-launch value QA sheet. Not for whether the tag fires or UTMs are clean — use conversion-signal-qa; not for cross-platform double-count de-dup — use attribution-reconciler; not for scoring R1/R2 — that is a scored veto in ad-account-auditor. 付费广告转化价值建模/利润出价/价值规则QA

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Audit an LLM eval pipeline and surface problems: missing error analysis, unvalidated judges, vanity metrics, etc. Use when inheriting an eval system, when unsure whether evals are trustworthy, or as a starting point when no eval infrastructure exists. Do NOT use when the goal is to build a new evaluator from scratch (use error-discovery, write-judge-prompt, or validate-evaluator instead).

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Identify tumor neoantigens from somatic variants with pVACtools (pVACseq/pVACfuse/pVACbind/pVACvector/pVACview) for personalized cancer vaccines and checkpoint biomarkers. Encodes the field's hard truth that binding prediction is the easy, near-solved part and single-digit-percent PPV lives downstream — so it centers clonality/CCF, HLA LOH (the silent invalidator), expression, proximal-variant phasing, agretopicity/foreignness quality, and the predicted->presented->immunogenic validation tiers. Use when nominating vaccine targets, ranking neoantigens, or building a tumor-to-candidate pipeline. Binding details in mhc-binding-prediction; ranking in immunogenicity-scoring.

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Capture and review Agent Skill observations, and create, run, diagnose, or iteratively improve Skill evaluations (evals) with the skill-up CLI. Use when the user asks to record explicitly attributed Skill usage or feedback; review observations or user-supplied traces/transcripts; turn an approved observation into a regression case; evaluate, test, regress, verify, fix, improve, iterate, or evolve a Skill; add or strengthen eval cases; write eval.yaml/case.yaml; run skill-up run/validate/list-cases/report/import/init; or migrate from Anthropic evals.json. Plugin observation capture/review require either the Codex skill-up plugin or an observer-enabled DSH skill-up plugin. User-supplied external evidence can be reviewed without a plugin; evaluation remains multi-engine.

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