「eval」の検索結果

Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.

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Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations.

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Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

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Inspect Caveman Cloud's eval-gated experiment lifecycle and block unsafe execution. Use when the user asks to start, approve, cancel, promote, or roll back a Caveman experiment, or asks what action an experiment's evidence supports. Read evidence first; do not execute lifecycle mutations until server-authoritative transition and evidence gates ship.

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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

Apex test patterns for @InvocableMethod agent actions: per-reason-code branch coverage, bulk safety, callout mocking, deterministic assertions. NOT for testing whether the agent routes to the right topic or answers well — use agentforce/agent-testing-and-evaluation. NOT for designing the error envelope the tests assert on — use agentforce/agent-action-error-handling.

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Configuring User Access Policies (UAP) to automatically assign or revoke permission sets and permission set groups based on user attributes. Use when automating permission provisioning on user create/update without Apex triggers. Covers policy configuration, filter criteria, evaluation order, and PSL assignment. Also covers booleanFilter OR logic, the `in` operator for multi-value filters, the `order` tiebreak between competing policies, actions incl. permission set / permission set group / permission set licence / package licence / queue / public group grant and revoke, the UserAccessChange audit object, and deploying the UserAccessPolicy metadata type. NOT for permission set design — use admin/permission-set-architecture. NOT for delegated user admin — use admin/delegated-administration.

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An Agentforce agent is moving from build or sandbox to live end-user traffic and the team needs a comprehensive readiness gate: coverage testing, Trust Layer config, guardrails, cost telemetry, observability, rate limits, permissions, rollout strategy, rollback plan, performance benchmarks. Triggers: 'we want to ship our Agentforce agent next week', 'pre-prod readiness review for our Service Agent', 'what do we need before turning the agent on for real customers', 'agent went live and is hallucinating, what should we have caught', 'cost monitoring for our internal sales agent', 'rollout strategy from internal pilot to GA'. NOT for the lighter five-block activation sign-off artifact — use agentforce/agent-deployment-checklist. NOT for authoring the guardrails themselves — use agentforce/agentforce-guardrails. NOT for building the test harness — use agentforce/agentforce-eval-harness. NOT for Trust Layer feature setup in isolation — use agentforce/einstein-trust-layer.

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Cross-tool decision matrix for field-update automation in Salesforce — Before-Save Flow vs After-Save Flow vs Apex Trigger vs the deprecated Workflow Rule + Field Update. Covers the recursion / re-entrancy rules, governor cost per pattern (Before-Save flow is governor-free for the same record), the order-of-execution slot each tool occupies, and the Workflow-Rule-to-Flow migration playbook for field-update actions. NOT for the full record-save order of execution — use apex/order-of-execution-deep-dive. NOT for building the record-triggered Flow once the tool is chosen — use flow/record-triggered-flow-patterns. Trigger keywords: WorkflowFieldUpdate, reevaluateOnChange, onCreateOrTriggeringUpdate, doesRequireRecordChangedToMeetCriteria, failedMigrationToolVersion, Migrate to Flow, workflow-meta.xml, field update deprecated, double writer, second trigger pass.

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Build the executive KPI dashboard for Agentforce: adoption, deflection, latency, cost, quality — KPI definitions, data sources, CRM Analytics lenses, alert thresholds. NOT for the platform's own session tracing, Agent Analytics and health monitoring — use agentforce/agentforce-observability. NOT for scoring agent answer quality offline — use agentforce/agentforce-eval-harness.

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Use when a subscriber admin is installing, upgrading, or rolling back a managed package (1GP or 2GP) sourced from AppExchange or a private install URL — covers pre-install evaluation, sandbox dry runs, license and dependency checks, the install/upgrade audit trail, post-install configuration the package's InstallHandler cannot perform, and uninstall fallback. NOT for building managed packages as an ISV (use devops/managed-package-development), unlocked-package development (use devops/unlocked-package-development), or AppExchange listing setup. Trigger keywords: InstalledPackage, installedPackages, securityType, activateRSS, sf package install, sf package installed list, PackageLicense, UserPackageLicense, AllowedLicenses, UsedLicenses, push upgrade, PackageSubscriber, namespace prefix, 04t, certified managed package limits.

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Flow Orchestration admin: stage configuration, step assignment, background steps, interactive steps, evaluation flows, work items, pause/resume. NOT for approval routing a standard approval process would handle — use admin/approval-processes.

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Use when scoring a list of business or solution requirements against the *actual* capabilities of a specific Salesforce org so each row can be classified Standard / Configuration / Low-Code / Custom / Unfit, given an effort tier (S/M/L/XL), a risk tag, and an AppExchange suggestion when applicable. Trigger keywords: fit gap salesforce requirements, score requirements against salesforce capabilities, salesforce capability matrix, classify requirement as standard config custom, fit-gap effort tier, AppExchange alternative for requirement. NOT for requirements elicitation (use admin/requirements-gathering-for-sf). NOT for architecture decisions on the GAP rows (use architect/solution-design-patterns and standards/decision-trees/). NOT for license or edition selection (use architect/license-optimization-strategy and architect/org-edition-and-feature-licensing). NOT for OmniStudio-specific fit-gap (use architect/omnistudio-vs-standard-decision).

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Use when gathering or evaluating requirements for a Salesforce Commerce Cloud digital storefront — branding strategy, content management approach, personalization, mobile experience, and accessibility compliance. Trigger keywords: SFRA branding, PWA Kit storefront, composable storefront, storefront accessibility, WCAG Commerce Cloud, overlay cartridge branding, mobile storefront, storefront personalization, content slots. NOT for building the site in Business Manager — use admin/b2c-commerce-store-setup. NOT for SCAPI design, Managed Runtime and caching strategy — use architect/headless-commerce-architecture.

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Identify, score, and prioritize Salesforce AI use cases before any implementation begins — opportunity identification, Impact-Effort matrix scoring, feasibility evaluation across Technical/Operational/Data/Risk dimensions, and ROI framing. NOT for the license checks and enablement steps once a use case is approved — use agentforce/agentforce-service-ai-setup or agentforce/agentforce-sales-ai-setup. NOT for making the data model AI-ready — use architect/ai-ready-data-architecture.

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Detects review-blocking configuration issues including sub-1.0 version numbers, beta in app name, staging endpoints, and missing demo credentials that prevent reviewers from evaluating the app, violating Guidelines 2.1 and 2.3.

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How to write good tests. Use when writing tests, improving test coverage, or evaluating test quality. Also invoked by other skills — BDD at RED phase, tdd-review at GREEN gate, refactor at PROTECT phase, and debug. Core test quality knowledge across all workflows.

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Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

Franchise Owner Playbook — franchise evaluation, SOP, multi-unit operations, franchisor relationship, ROI analysis สำหรับเจ้าของแฟรนไชส์ไทย

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Influencer marketing AI — brief, pitch, rate evaluation, performance review แบบ data-driven

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Reporting workflow for a working journalist, using web research and Apify's X scraper (social signals). Onboards the journalist, monitors their beat and builds digests, evaluates story pitches, finds and vets sources, and prepares interviews. Use for any newsroom task, such as "what's new on my beat", "is this pitch any good", "who should I talk to about X", "prep me for this interview", or "turn these notes into a draft".

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Expert in the medieval problem of universals, covering Platonic realism, Aristotelian moderate realism, and Ockhamist nominalism with modern analytical perspectives

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Expert in historical alchemy, Hermetic philosophy, and symbolic transformation from medieval to modern esoteric traditions

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。