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Manage Data Quality Lookups Setup Task Guidance

Organization
oracle
Manage Data Quality Lookups Setup Task Guidance

Provides task-specific setup guidance for Manage Data Quality Lookups under the Data Quality Foundation functional area.

Overview

Publisheroracle
RepositoryFusion-Setup-Configuration-Registry
Skill nameManage Data Quality Lookups Setup Task Guidance
Stars
112
Forks
26
Bundled files
7
LicenseUPL-1.0
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by oracle on GitHub. Read the source before you install it.

Installation

Install the Manage Data Quality Lookups Setup Task Guidance AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/oracle/Fusion-Setup-Configuration-Registry/tree/main/pillars/cx/customer-data-management/data-quality-foundation/manage-data-quality-lookups
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/oracle/Fusion-Setup-Configuration-Registry.git /tmp/Fusion-Setup-Configuration-Registry
mkdir -p .claude/skills
cp -r /tmp/Fusion-Setup-Configuration-Registry/pillars/cx/customer-data-management/data-quality-foundation/manage-data-quality-lookups .claude/skills/oracle-manage-data-quality-lookups-setup-task-guidance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Manage Data Quality Lookups Setup Task Guidance in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Manage Data Quality Lookups Setup Task Guidance on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Manage Data Quality Lookups Setup Task Guidance is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Manage Data Quality Lookups Setup Task Guidance

Purpose

Provides task-specific setup planning, routing, export, import, and validation guidance for Manage Data Quality Lookups under Data Quality Foundation.

Setup Task Skill Contract

  • task_code: ZCQ_MANAGE_DATA_QUALITY_LOOKUPS
  • task_name: Manage Data Quality Lookups
  • parent_skill_id: cx.customer-data-management.data-quality-foundation
  • pillar: CX
  • offering: Customer Data Management
  • functional_area: Data Quality Foundation
  • functional_area_code: ORA_ZCQ_DATA_QLTY_FOUNDATION
  • available_flag: Y
  • export_import_supported_flag: Y
  • csv_export_import_supported_flag: Y
  • source_catalog: knowledge/setup-task-catalog/release/setupTasksAll.json

Usage

Use this skill when planning, sequencing, exporting, importing, or validating setup data for Manage Data Quality Lookups under Data Quality Foundation.

Setup Task Metadata

  • Task name: Manage Data Quality Lookups
  • Task code: ZCQ_MANAGE_DATA_QUALITY_LOOKUPS
  • Available: Y
  • Export/import supported: Y
  • CSV export/import supported: Y
  • CSV export/import routing: supported

CSV Export, Import, and Validation Workflow

CSVExportImportSupportedFlag is Y for this task, so route task setup data work through the shared skills:

  1. Export setup task data with shared.setup-export.task-level-export.
  2. Validate setup task data with shared.validation.setup-data-validator.
  3. Validate reference data with shared.validation.reference-data-validator.
  4. Import setup task data with core.data-loader.

Use this task metadata when invoking those skills:

  • Offering: Customer Data Management
  • Functional area / Setup Object: Data Quality Foundation
  • Setup task name: Manage Data Quality Lookups
  • Setup task code: ZCQ_MANAGE_DATA_QUALITY_LOOKUPS

Inputs

  • implementation_objective
  • project_context
  • setup_task_scope
  • setup_data_artifacts

Outputs

  • setup_task_plan
  • setup_data_routing
  • validation_checkpoints
  • skill_run_record
  • token_usage_record

Implementation Notes

Use the parent functional-area skill cx.customer-data-management.data-quality-foundation for functional-area sequencing and scope decisions. Track token usage for any generated project artifact or skill-run record using the manifest policy.

Task-specific lookup baseline

The exact-task Fusion page establishes this closed 21-type Standard lookup inventory:

Lookup typeScope
ZCQ_IIR_MATCH_TOLERANCEMatch tolerance
ZCQ_ADDR_CLEANSED_STATUSAddress cleansing status
ZCQ_BATCH_MATCH_MODEBatch match mode
ZCQ_PARAMETER_LEVELParameter level
ZCQ_PARAMETER_TYPEParameter type
ZCQ_SORT_BY_SCORESort by score
ZCQ_BATCH_PURGE_MODEBatch purge mode
ZCQ_BATCH_STATUSBatch status
ZCQ_BATCH_TYPEBatch type
ZCQ_IIR_ASM_CHARSETIIR address cleansing character set
ZCQ_IIR_ASM_FORCE_COUNTRYIIR forced country
ZCQ_IIR_ASM_VAL_MODEIIR address validation mode
ZCQ_OPERATIONSData quality operations
ZCQ_ORG_MATCH_OPTION_CODEOrganization match option
ZCQ_ASM_ATTRIBUTESAddress cleansing attributes
ZCQ_BATCH_REQUESTOR_TYPEBatch requestor type
ZCQ_ENTITYData quality entity
ZCQ_IIR_SEARCH_WIDTHIIR search width
ZCQ_PARAMETER_CARDINALITYParameter cardinality
ZCQ_PER_MATCH_OPTION_CODEPerson match option
ZCQ_IIR_ASM_PREF_LANG_TYPEIIR preferred language type

Do not infer additional members from the ZCQ_ prefix, module, or meaning. A current exact GET must reconfirm Standard category, configuration level, codes, seeded origin, and REST-described fields before a live operation.

Supported operations and safety contract

  • Read-only listing and exact type/code retrieval are supported without approval after task-membership resolution.
  • Lookup-type creation/deletion, identity changes, category changes, module changes, configuration-level changes, REST-security changes, and seeded-identity changes are unsupported.
  • Custom-code create, update, or delete is conditional on current configuration-level rules, CreatedBy seed evidence, and current REST describe. Never silently upsert and reject custom codes beginning with ORA_.
  • Before a manual mutation, show one exact redacted preview bound to environment, method, endpoint, before/after state, payload, impact, and fingerprint; require explicit approval; send exactly one request through the shared Fusion REST client; never automatically retry; verify separately with GET.
  • Export with shared.setup-export.task-level-export using exact TaskCode ZCQ_MANAGE_DATA_QUALITY_LOOKUPS. Validate with both shared validators and route import only through core.data-loader.
  • An FSM import must preserve immutable ZIP bytes, contain exactly one safe ASM_SETUP_CSV_METADATA.xml, identify only this exact TaskCode, pass the Core Data Loader Task Hook, and retain an approval-bound SHA-256 envelope through submission.

See ora-resource/ for the executable validation, lookup, design, and error rules.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Manage Data Quality Lookups Setup Task Guidance AI skill do?

Provides task-specific setup guidance for Manage Data Quality Lookups under the Data Quality Foundation functional area.

Why use Manage Data Quality Lookups Setup Task Guidance on TypingMind?

Because you install it once and use it with any model. Manage Data Quality Lookups Setup Task Guidance is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Manage Data Quality Lookups Setup Task Guidance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oracle/Fusion-Setup-Configuration-Registry/tree/main/pillars/cx/customer-data-management/data-quality-foundation/manage-data-quality-lookups. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Manage Data Quality Lookups Setup Task Guidance?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Manage Data Quality Lookups Setup Task Guidance?

As many as you like. As long as a model supports skills, you can use Manage Data Quality Lookups Setup Task Guidance with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Manage Data Quality Lookups Setup Task Guidance AI skill free?

Yes. It is published on GitHub by oracle under the UPL-1.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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