Manage Contact Descriptive Flexfields Setup Task Guidance logo

Manage Contact Descriptive Flexfields Setup Task Guidance

Organization
oracle
Manage Contact Descriptive Flexfields Setup Task Guidance

Provides task-specific setup guidance for Manage Contact Descriptive Flexfields under the Trading Community Foundation functional area.

Overview

Publisheroracle
RepositoryFusion-Setup-Configuration-Registry
Skill nameManage Contact Descriptive Flexfields Setup Task Guidance
Stars
112
Forks
26
Bundled files
5
LicenseUPL-1.0
Links
  • 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.

  • 5 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 Contact Descriptive Flexfields 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/trading-community-foundation/manage-contact-descriptive-flexfields
  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/trading-community-foundation/manage-contact-descriptive-flexfields .claude/skills/oracle-manage-contact-descriptive-flexfields-setup-task-guidance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Manage Contact Descriptive Flexfields 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 Contact Descriptive Flexfields 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 Contact Descriptive Flexfields 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 Contact Descriptive Flexfields Setup Task Guidance

Purpose and Boundary

Use this skill to export, import, migrate, validate, or resume status for the complete FSM setup package of Manage Contact Descriptive Flexfields. The fixed task code is HZ_MANAGE_CONTACT_DESCRIPTIVE_FLEXFIELDS. Use this skill when planning, sequencing, exporting, importing, or validating setup data for Manage Contact Descriptive Flexfields under Trading Community Foundation.

Do not create, update, delete, deploy, or inspect individual flexfields, contexts, segments, value sets, or attributes. Do not use direct descriptive flexfield REST CRUD, task-local HTTP, loose CSV, templates, filters, or partial package migration. The shared FSM exporter owns export validation and execution. Core Data Loader owns every import, including adapter, endpoint, payload, submission, status, and retry-policy selection.

Fixed Task Context

  • Pillar: CX
  • Offering: Customer Data Management
  • Functional area: Trading Community Foundation
  • Functional area code: ORA_HZ_CDM_FOUNDATION
  • Task name: Manage Contact Descriptive Flexfields
  • Task code: HZ_MANAGE_CONTACT_DESCRIPTIVE_FLEXFIELDS
  • Export/import supported: Y
  • CSV export/import supported: Y
  • Data Loader import mode: FSM

Never accept a caller override for the task name or code. Use the parent skill for broader functional-area sequencing.

Oracle Source Boundary

Use these Oracle sources for deployment and migration guardrails:

Oracle states that only Deployed or Deployed to Sandbox flexfields are eligible to be moved. Treat that as Fusion migration behavior, not as a manual status-evidence prerequisite for starting an FSM export. Do not ask the user for source deployment status, observation time, or an evidence reference before export; rely on the export process and its ProcessLog to report exportability. Descriptive-flexfield sandbox testing remains required before manual publication. Import can change deployment status and can submit affected flexfields for redeployment; neither an accepted import nor automatic redeployment proves that target deployment and functional verification passed. Do not apply extensible-flexfield background-deployment queue behavior here.

Supported Operations

  1. export: authorize and run one complete, unfiltered, non-template task export.
  2. import: validate and authorize one complete, unchanged FSM ZIP and run one import.
  3. migrate: finish and persist source export, then perform separate target preflight and approval before import.
  4. validate: validate fixed task context, operation-specific routing, package identity when supplied, and approval readiness without submission.
  5. status: resume polling or retrieve results for one persisted ProcessId; never create another process.

Export and Import Adapter Contract

For export, preserve the existing export route: validate the fixed task and whole-task scope, display one exact task-level export preview, obtain explicit approval for that environment and process creation, and invoke shared.setup-export.task-level-export directly. Do not route export through core.data-loader, approved-loader-payload, or executionRoute=data-loader. An export never requires a pre-existing ZIP path or SHA-256.

Use this fixed export final data:

text
operation=export
task_code=HZ_MANAGE_CONTACT_DESCRIPTIVE_FLEXFIELDS
task_name=Manage Contact Descriptive Flexfields
offering_name=Customer Data Management
functional_area_name=Trading Community Foundation
template_only=false
export_criteria=[]
output_dir=project/{project_id}/exports/customer-data-management/trading-community-foundation/manage-contact-descriptive-flexfields/
execution_adapter=shared.setup-export.task-level-export
wait_seconds=300
poll_interval=10

After export approval, invoke shared.setup-export.task-level-export exactly once. The shared exporter owns the export POST, ProcessId, polling, FileContent, and ProcessLog behavior. After download, compute and persist the exported ZIP's SHA-256. Do not implement task-local export HTTP.

For import, route exclusively through core.data-loader. Require one unchanged ZIP and supply only this task context to Core Data Loader:

text
operation=import
task_code=HZ_MANAGE_CONTACT_DESCRIPTIVE_FLEXFIELDS
task_name=Manage Contact Descriptive Flexfields
setup_data_zip_path=<validated ZIP path>
setup_data_zip_sha256=<SHA-256 of the exact ZIP bytes>

Require a valid ZIP signature and exactly one case-sensitive member basename ASM_SETUP_CSV_METADATA.xml. Require its single task identity to equal the fixed task code. Preserve the archive byte for byte. Do not construct or change an import payload or request a revision-mismatch override.

Let Core Data Loader prepare the final immutable artifact, invoke its data-load Task Hook, build the approval preview, and obtain the user's separate explicit approval. The Task Hook validation envelope must remain bound to the exact ZIP SHA-256. Core Data Loader then owns UCM upload, initiation-payload construction, endpoint and FSM adapter selection, accepted-request reporting, status diagnostics, and retry policy. This pillar skill must not select or invoke an import adapter, endpoint, routing field, payload builder, or retry behavior.

Post-Import Deployment Verification

After a terminally successful import, require target deployment evidence and a functional verification result:

  • Return import_succeeded_deployment_verified only when target status is Deployed or Deployed to Sandbox and the contact DFF functional test passed in the named target environment.
  • Return import_succeeded_deployment_pending when import succeeded but target status or functional verification is missing, nonterminal, Edited, Patched, or Error. Report the manual validation, sandbox deployment/test, publication, or redeployment action required; do not perform it.
  • Return import_failed only when the FSM import process fails. Retrieve and persist ProcessLog when available.

Never collapse import acceptance, import process success, automatic redeployment submission, target deployment status, UI rendering, and functional verification into one success claim.

Preflight and Approval

Before any live export or import:

  1. Resolve a valid project, exact environment, fixed task context, durable output paths, and task-local compiled rules.
  2. Authenticate separately. If a cache-managed token fails on a read-only preflight, refresh once and repeat only that GET. A second rejection blocks submission.
  3. Confirm live task discovery returns the fixed task code and CSVExportImportSupportedFlag=Y. Do not reject solely because offering or functional-area fields are absent in the live row.
  4. For export, validate the fixed whole-task non-template contract. Do not ask for deployment status, a ZIP path, or a SHA-256 before export.
  5. For import, validate the unchanged archive, exact metadata identity, hash, and target, then hand control exclusively to Core Data Loader.
  6. For export, display one redacted task-level preview containing the environment, task, whole-task scope, output path, adapter, execution options, and one-process impact. Bind approval to those values and then call the shared exporter directly.
  7. For import, let Core Data Loader display the immutable preview and obtain approval bound to its environment, task, ZIP/hash, validation envelope, and impact. Any changed import-bound value restarts Core Data Loader validation, Task Hook, preview, and approval.

Submission, Polling, and Reconciliation

Persist an external identifier returned by the owning exporter or Core Data Loader immediately in an append-only run record. Delegate polling, log retrieval, and status semantics to that owner. On timeout, preserve the identifier and safe resume stage; never submit a replacement process.

Never automatically retry an export or import mutation after 401, 403, timeout, connection closure, or an uncertain response. For import, follow only Core Data Loader's reconciliation and status contract. For export, reconcile using read-only process lookup for the fixed task and run-start window:

  • One matching process: persist and resume its ProcessId.
  • No matching process: record not_created; a new POST needs fresh approval.
  • Multiple or unidentifiable matches: record ambiguous and fail closed.

Diagnostics and Results

Classify failures as input_validation, catalog_or_metadata_mismatch, auth_expired_or_invalid, authorization_or_privilege, transport_or_environment, fusion_api_error, process_timeout, process_failed, artifact_persistence, approval_blocker, or deployment_verification.

Report the exact task, environment, operation, owning execution skill, ProcessId, terminal or last-known process status, artifact paths, ZIP SHA-256 when applicable, deployment-verification result, warnings, blockers, and one safe next action. Never print or persist tokens, secrets, Authorization headers, token-cache contents, full base64 payloads, or sensitive environment values.

Refusal Rules

Refuse:

  • Direct descriptive flexfield REST CRUD or a task-local endpoint/script.
  • Individual context, segment, value-set, attribute, deployment, or UI changes.
  • Template/spec exports, export criteria, filters, or partial migration.
  • Loose CSV, an edited/repacked ZIP, missing or ambiguous metadata identity, revision mismatch override, task-code override, or changed approved artifact.
  • Task-local import adapter, endpoint, routing-field, payload, or retry selection.
  • A new submission while a previous response or ProcessId is uncertain.
  • A complete-success claim without target deployment and functional evidence.

Golden Scenarios

ScenarioExpected result
Export the complete task from TESTDo not ask for deployment evidence or a pre-existing ZIP/hash; approve the fixed whole-task contract, submit once through the shared exporter, and persist ZIP, hash, ProcessId, and status
Import the unchanged ZIP into UATValidate exact task metadata and hash, hand the archive to Core Data Loader, approve its immutable preview, let it execute and report status, and classify deployment verification separately
Migrate TEST to UATFinish source export before separate target validation and import approval; return complete only after target deployment and functional verification
Export a template or one flexfieldRefuse without a Fusion call
Edit a segment through RESTRefuse because direct DFF CRUD is unsupported
Import succeeds but target is PatchedReturn import_succeeded_deployment_pending and report manual validation/redeployment and sandbox-test action
Polling times outPreserve the same ProcessId and allow status-only continuation; never resubmit

Ownership and Review

  • Owner: CX Customer Data Management pillar team.
  • Functional reviewer: CX Customer Data Management Pillar Lead or Trading Community Foundation SME.
  • Framework reviewer: FSCR A-Team/core reviewer.
  • QA reviewer: required for FSM routing, approval, deployment, or verification changes.

Track token usage for generated project artifacts and skill-run records using the manifest policy.

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 Contact Descriptive Flexfields Setup Task Guidance AI skill do?

Provides task-specific setup guidance for Manage Contact Descriptive Flexfields under the Trading Community Foundation functional area.

Why use Manage Contact Descriptive Flexfields Setup Task Guidance on TypingMind?

Because you install it once and use it with any model. Manage Contact Descriptive Flexfields 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 Contact Descriptive Flexfields 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/trading-community-foundation/manage-contact-descriptive-flexfields. 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 Contact Descriptive Flexfields 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 Contact Descriptive Flexfields Setup Task Guidance?

As many as you like. As long as a model supports skills, you can use Manage Contact Descriptive Flexfields 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 Contact Descriptive Flexfields 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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