'mapping' 검색 결과

Apply a set of Rosetta Stone attribute mappings to a Narrative dataset by wrapping them in a one-shot workflow that calls the `CreateRosettaStoneMappingsIfNotExist` task. Consumes the structured output of `/generate-rosetta-stone-mappings`, normalizes the generator's snake_case to the workflow task's camelCase, re-validates every expression against the dataset's current schema, gates on user approval, submits via `narrative_workflows_create`, polls the triggered run, and reports per-mapping created / conflict / failed. Use when: "apply these mappings to dataset N", "create the Rosetta Stone mappings I just generated", "push the mappings I saved earlier to <dataset>", "productionize this mapping list", "submit the suggested_mappings array". (narrative-common)

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Map Delphi classes to a relational database using TMS Aurelius ORM attributes. Use when the user asks to create entity classes, add Aurelius mapping to existing classes, fix or review mapping attributes, explain how a class is mapped, or work with associations, inheritance, automapping, nullable fields, blobs, or composite identifiers. Triggers on requests like "create Aurelius entities for...", "map this class to Aurelius", "add ORM mapping", "fix the mapping on this class", "how do I map a one-to-many in Aurelius".

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Generate, evaluate, and improve Rosetta Stone attribute mappings for a Narrative dataset. Use when: "map this dataset to Rosetta Stone", "suggest normalized attributes for dataset N", "evaluate the mappings on dataset N", "why is this mapping low confidence", "fix this expression", "improve this NQL mapping expression". (narrative-common)

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Turn user data and interviews into research-backed personas, or representative user profiles. The toolkit also supports mapping user journeys, planning usability tests, and combining research findings to guide and validate design decisions.

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• Creating personas from user data and interviews
• Mapping the steps of a customer journey
• Planning usability tests to validate a design

Find code components that match Figma design components by comparing names, structure, and settings. Presents candidates for approval, then creates Code Connect mappings, explicit links between design components and their implementations.

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• Link a Figma button to its code component
• Find unconnected components within a frame
• Compare similar implementation candidates

Build or review tables that match patent claim elements or civil legal requirements to product information and evidence. Each mapping cites a precise source location, while a separate gap list identifies evidence still needed for attorney analysis.

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• Mapping patent claims to an accused product
• Comparing patent claims with prior art
• Finding missing evidence for civil claims or defenses

Turn a Figma design into code that fits an existing project. Reuse its components and shared style values, follow designer notes and component mappings, and adapt Figma's reference output to the project's framework and conventions.

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• Implementing a screen from a Figma design
• Reusing existing project components in a design implementation
• Applying designer notes and shared style values

Provides patterns for unit testing mappers, converters, and bean mappings. Validates entity-to-DTO and model transformation logic in isolation. Generates executable mapping tests with MapStruct and custom converter test coverage. Use when writing mapping tests, converter tests, entity mapping tests, or ensuring correct data transformation between DTOs and domain objects.

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Guides systematic mapping of international personal data flows across an organisation. Covers system-by-system inventory methodology, third-party identification, transfer mechanism assignment, gap analysis, and data flow visualisation. Keywords: data flow mapping, international transfers, data inventory, transfer register, cross-border data flows.

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Harmonises data classification across jurisdictions mapping GDPR special categories vs CCPA sensitive PI (1798.140(ae)) vs HIPAA PHI (160.103) vs LGPD sensitive data (Art. 5-II). Provides cross-regulation mapping matrix for multinational compliance. Keywords: cross-jurisdiction, GDPR, CCPA, HIPAA, LGPD, sensitive data, multinational, classification mapping.

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Expert knowledge for real-time and baked lighting in games - from cinematography fundamentals to engine-specific optimization, covering GI, time-of-day, volumetrics, and platform-aware lighting pipelinesUse when "lighting, light design, baked lighting, realtime lighting, lightmap, lightmapping, light probe, reflection probe, global illumination, GI, ambient occlusion, shadow, shadow cascade, time of day, day night cycle, volumetric fog, volumetric lighting, god rays, HDR, tonemapping, bloom, exposure, emissive, area light, Lumen, Enlighten, ray tracing, RTGI, light baking, lighting, global-illumination, lightmapping, shadows, GI, light-probes, reflection-probes, HDR, tonemapping, volumetric, fog, time-of-day, baked, realtime, mixed-lighting, lumen, enlighten, radiosity, ray-tracing, RTGI" mentioned.

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Configuring Salesforce lead management and conversion in Setup: lead settings, web-to-lead, conversion field mapping, lead queues, auto-response rules, lead processes. Trigger keywords: web-to-lead, lead conversion, lead field mapping, lead settings, lead process, lead queue, lead auto-response. NOT for Apex that controls what conversion creates - use apex/lead-conversion-customization. NOT for lead assignment rule logic - use admin/assignment-rules. NOT for duplicate rule configuration - use admin/duplicate-management. Also covers: LeadConvertSettings objectMapping XML, LeadConfigSettings, LeadStatus StandardValueSet converted flag, lead process BusinessProcess, Database.convertLead bulk conversion limits.

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MyBatis를 사용하는 Java 데이터 저장·조회 코드를 설계하고 검토합니다. 결과 매핑, 동적 SQL과 입력 안전성, 트랜잭션, 페이지 나누기와 검색 성능을 다룹니다.

• 매퍼와 XML의 대응 관계 설계
• 동적 SQL과 입력값 안전성 확인
• 여러 갱신을 묶는 트랜잭션 검토

Fill web forms from a JSON list of field names and values, using saved templates or page labels to locate inputs. Optionally submit the form, save new field mappings, and redact values from recorded actions.

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• Filling signup and contact forms
• Reusing templates for recurring submissions
• Saving field mappings for a new form

Monitor local network traffic for ARP spoofing, where false address mappings can redirect traffic. Use ARPWatch, Wireshark, switch inspection settings, and Python monitoring to flag address changes, duplicate IP claims, gateway impersonation, and unusual ARP volumes.

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• Investigating suspected interception on a local network
• Monitoring changes in IP-to-MAC address mappings
• Checking duplicate IP claims and gateway impersonation

Map intrusion evidence to the seven stages of the Lockheed Martin Cyber Kill Chain, a model of attack progression. Show where defenses worked or missed activity, and recommend prioritized controls that could interrupt attacks earlier.

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• Mapping attack progression after an incident
• Finding detection gaps at each attack stage
• Planning layered defenses to stop attacks earlier

Guide a team through questions about users, workflows, and priorities to create a user story map. Organize activities and tasks, then define a minimum viable product and later releases that each cover the full workflow.

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• Facilitating a team story mapping workshop
• Reorganizing a flat backlog around user workflows
• Defining the scope of a minimum viable product

Guide a workshop that maps a specific customer’s experience from start to finish. Capture stages, actions, thoughts, emotions, and pain points, then produce a customer journey map and a prioritized list of improvement opportunities.

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• Mapping the onboarding experience for new customers
• Finding obstacles between trial signup and first value
• Reviewing support experiences for customers at risk of leaving

Search ClinVar and NCBI Variation for genetic variants, or look up records using VCV, RCV, SCV, and RefSNP identifiers. Get concise summaries, check identifier mappings, and save full JSON responses when needed.

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• Searching ClinVar for a genetic variant
• Looking up VCV, RCV, SCV, or RefSNP records
• Checking mappings between variant identifiers

Organization-grade identity-fabric mapping: tenant/federation fingerprinting and the pre-auth user-ENUMERATION oracle methodology — enumeration and fingerprint only, never credential submission. Covers domain-to-tenant resolution (Microsoft getuserrealm.srf Managed/Federated namespace check, Entra OIDC metadata tenant-GUID extraction, Autodiscover v2), keyless Microsoft tenant-federation mapping (GetFederationInformation SOAP -> sibling-domain discovery, discover-only ROE, FEDERATED_WITH provenance edge held out of attack-path pivoting), Okta org-slug derivation + OIDC fingerprint + governed custom-domain enumeration, ADFS passive/active fingerprint + version inference, Google Workspace MX-correlated detection, generic OIDC (Auth0/Keycloak/Ping Identity/OneLogin/Duo) discovery, SAML metadata (5 paths), Azure AD Seamless-SSO Negotiate-challenge detection, Microsoft Defender for Identity (MDI) sensor-API presence check, the user-enumeration oracle methodology for Microsoft GetCredentialType (IfExistsResult semantics: exists / doesn't-exist / exists-in-federated-tenant / throttled) and Okta /api/v1/authn (errorCode differential), Medium-detectability discipline with a hard 20-candidate-per-tenant cap and admin/role interest-based ranking, and name x confirmed-email-pattern login-candidate synthesis that FAILS CLOSED with zero output when no org pattern is confirmed. Grounded directly in a production ASM implementation's sso_idp.py, tenant_recon.py, and core/email_patterns.py modules. Deepens — does not duplicate — offensive-osint skill's Identity Fabric endpoint reference with the tenant-federation MAP, the oracle WORKFLOW, and the candidate-SYNTHESIS methodology that reference lacks. Use when fingerprinting an organization's identity provider, mapping its tenant/federation boundary, running an authorized pre-auth user-enumeration pass, or synthesizing login candidates from harvested names to feed that oracle — never for password spray, credential submission, or auth bypass.

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Set up player input in Unreal Engine 5 with Enhanced Input: Input Actions, Input Mapping Contexts, modifiers and triggers, adding the mapping context, and binding actions by ETriggerEvent. Use when wiring movement/look/jump input, creating IA_/IMC_ assets, binding in C++ or Blueprints, or when the user mentions Enhanced Input, Input Mapping Context, Input Action, IA_/IMC_, or ETriggerEvent.

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Provide system alias mapping for Search CLI. Invoke this skill when user mentions "Search CLI", "search_cli", or tries to execute search_cli commands.

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User story mapping for backlog management and outcome-based prioritization. Load during Phase 2.5 (User Story Mapping) to produce story-map.md and prioritization.md.

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Use when you need to design, review, or improve validation in Quarkus applications — including Bean Validation on JAX-RS resources, @Valid on parameters and CDI beans, constraint groups, @ConfigMapping validation, custom constraints, nested DTO validation, and ExceptionMapper-based error mapping. This should trigger for requests such as Add validation support in Quarkus; Review Quarkus validation rules; Improve request validation in Quarkus REST APIs; Add custom validation constraints in Quarkus; Validate Quarkus @ConfigMapping properties. Part of Plinth Toolkit

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