「definitions」の検索結果

Generates NeMo Guardrails Colang (.co) files and YAML config blocks from a plain-language description of a chatbot's purpose, allowed behaviors, and constraints. Use this skill whenever a user wants to build guardrails for a chatbot, define allowed intents for an LLM, create an AI firewall with NeMo Guardrails, generate Colang flow definitions, or configure a semantic allow-list for a bot. Trigger this skill even when the user just describes what their bot should and shouldn't do — generating the Colang and YAML is almost always what they need next.

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Supreme policy layer governing all agent behavior. Autonomy, one-line prompt interpretation, speed standards, emphasis signal processing, cross-skill coordination, done definitions, conflict resolution. Loaded every prompt.

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。

TanStack Table v8 patterns - useReactTable, column definitions, sorting, filtering, pagination, row selection, virtual scrolling, server-side data

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。

Zod schema validation patterns for TypeScript - schema definitions, type inference, refinements, transforms, discriminated unions

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。

SurrealDB multi-model database - SurrealQL queries, record links, graph relations, live queries, schema definitions, authentication, TypeScript SDK

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Structured content platform — GROQ queries, schema definitions, @sanity/client, Portable Text, image handling, real-time listeners, mutations, TypeGen

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。

Sequelize ORM, model definitions, associations, queries, transactions, migrations

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 reusable malware configuration extractors by applying a declarative JSON spec (offsets, decode layers, field definitions) to a sample to produce structured, defanged config. Activates for requests to build a config extractor, write a reusable family config parser, or run a spec-driven configuration extraction.

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Connect to and query WRDS (Wharton Research Data Services) from any research project. Use this skill whenever the user needs to download, query, or explore data from WRDS — including Compustat, CRSP, FactSet, I/B/E/S, or any other WRDS-hosted database. Also trigger when the user mentions WRDS tables, WRDS libraries, or wants to look up variable definitions or coverage in WRDS datasets. Do NOT trigger for general SQL or database questions unrelated to WRDS.

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Use when a task needs the judgment of a Chief Data Officer — resolving conflicting metric definitions across dashboards, deciding whether a dataset should be retained or purged, assigning data ownership for a system feeding regulatory or board reporting, sizing a privacy/breach risk against a proposed data collection, or auditing data readiness before an AI/ML initiative kicks off.

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Engineer the full context a model sees — system prompts, retrieved knowledge, tool definitions, state, and history as one designed artifact. Use when moving beyond prompt tweaks to systematic context design.

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Coordinate teams of role-based agents — role definitions, task delegation, sequential and hierarchical workflows, and shared memory. Use when a job naturally splits into specialist roles collaborating.

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Maps the entire API surface of a codebase -- route definitions, middleware chains, auth requirements, request/response types, deprecated endpoints, orphaned endpoints, and cross-endpoint inconsistencies..

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Write a data schema specification document. Use when the user says "schema spec", "document this schema", "schema design doc", "data model spec", "table spec", "field definitions", "schema contract", "data dictionary", "define these fields", or needs to formally document a database schema, event schema, or API payload schema - even if they don't explicitly say "schema spec".

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Generate a data dictionary documenting entities, fields, and business rules. Use when the user says "data dictionary", "document the data model", "what fields are in this table", "data definitions", "field descriptions", "CRUD matrix", "entity relationship", "data catalogue", "what data does this system store" - even if they don't explicitly say "data dictionary".

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Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation. Use for attribution audit, attribution models, conversion windows, requests to add or total Meta and Google conversions, incompatible reporting-window aggregation, GA4 attribution, MMP review, AppsFlyer, Adjust, Branch, Singular, or cross-platform discrepancies.

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Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.

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Authoring and managing Agentforce agent definitions using the declarative Agent Script DSL (.agent files) and associated metadata types, including the Agent Script language for the new Agentforce Builder (hybrid-reasoning -> logic vs | prompt instructions, @actions/@subagent/@variables references, subagents). Use when creating agents in source control, writing or debugging Agent Script, debugging agent metadata, or understanding the metadata lifecycle of GenAiPlugin/GenAiPlanner/BotVersion types. Triggers: 'how do I deploy an Agentforce agent using source control', 'convert an agent topic to a subagent', 'what metadata types make up an Agentforce agent', 'agent test run command failing in CI pipeline', 'GenAiPlugin vs GenAiPlanner metadata relationship', 'Agent Script logic vs prompt instructions'. NOT for Apex-based agent actions — use agentforce/custom-agent-actions-apex. NOT for clicking the agent together in the Builder UI — use agentforce/agentforce-agent-creation.

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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 this skill when designing or documenting a lead scoring model in Salesforce Sales Cloud or Account Engagement: qualifying criteria, MQL/SQL threshold definitions, scoring dimensions (demographic, firmographic, behavioral), and sales handoff SLA. NOT for configuring the scoring, grading, and automation rules in Account Engagement — use admin/mcae-lead-scoring-and-grading. NOT for the whole marketing program's lifecycle stages and platform scope — use admin/marketing-automation-requirements.

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Use this skill when gathering, documenting, or validating requirements for a Salesforce marketing automation program — covering MCAE (Account Engagement / Pardot) lifecycle stages, MQL/SQL threshold definitions, scoring model specifications (sources, weights, decay, ceiling), handoff notification design, CRM field updates on status change, and sales SLA. Trigger keywords: MQL criteria, marketing-to-sales handoff, lead lifecycle, scoring requirements, automation program requirements, Marketing Cloud Automation Studio scope. NOT for building the scoring and grading rules in MCAE — use admin/mcae-lead-scoring-and-grading. NOT for a Sales-Cloud composite score built from formula fields — use admin/lead-scoring-requirements.

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Use this skill when configuring MCAE (Account Engagement / Pardot) lead scoring models, grading profiles, score decay rules, or automation rules that fire on score/grade thresholds. Covers: scoring point values per activity, score decay for inactivity, Profiles for fit grading, combined MQL definitions (Score + Grade), and automation rules vs completion actions. NOT for defining the MQL model before build — use admin/lead-scoring-requirements. NOT for Engagement Studio nurture programs — use admin/lead-nurture-journey-design.

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Use this skill when an admin needs to create an Einstein Discovery story in CRM Analytics Studio, configure prediction definitions, deploy writeback fields, set up what-if analysis, or manage model refresh and activation. Trigger keywords: Einstein Discovery story, prediction definition, writeback field, CRM Analytics Studio, model refresh, what-if analysis, bulk scoring, prediction field, 1OR prefix. NOT for the Einstein Discovery Flow action or model-health monitoring in Model Manager — use admin/einstein-discovery-deployment. NOT for Einstein Prediction Builder, a separate product needing no CRM Analytics license — use agentforce/einstein-prediction-builder. NOT for programmatic scoring through the Connect REST API — use agentforce/einstein-discovery-development.

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Use this skill to design, configure, and troubleshoot Salesforce Entitlement Management on Cases: entitlement processes, milestone definitions, recurrence types, milestone actions (success/warning/violation), business hours assignment, and entitlement templates. Covers the deployable EntitlementProcess / MilestoneType / EntitlementTemplate / EntitlementSettings metadata, signed timeLength time triggers, recurrenceType semantics, process versioning, and how a milestone actually completes. Trigger keywords: entitlement process, milestone, SLA timer, milestone tracker, first response SLA, time trigger, recursChained, CaseMilestone, EntitlementId, SlaProcess, stopped clock. NOT for SLA milestones on Field Service work orders — use admin/fsl-sla-configuration-requirements. NOT for time-based case escalation rules — use admin/escalation-rules. NOT for the business-hours calendar itself — use admin/business-hours-and-holidays.

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。