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Bulk User Role Provisioning

Organization
oracle
Bulk User Role Provisioning

Prepares Oracle Fusion User/UserRole HDL sources, resolves missing role codes and person numbers through core REST services, and delegates approved HDL import, status, and LDAP follow-up to the owning core and Common-pillar skills.

Overview

Publisheroracle
RepositoryFusion-Setup-Configuration-Registry
Skill nameBulk User Role Provisioning
Stars
112
Forks
26
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Bulk User Role Provisioning 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/common/security-console/bulk-user-role-provisioning
  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/common/security-console/bulk-user-role-provisioning .claude/skills/oracle-bulk-user-role-provisioning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bulk User Role Provisioning 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 Bulk User Role Provisioning 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 Bulk User Role Provisioning 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.

Bulk User Role Provisioning

Purpose and service ownership

Use this Common-pillar Security Console skill for controlled bulk User/UserRole HDL provisioning. It owns source preparation, validation checkpoints, and cross-skill handoff records. It never calls Fusion REST, a loader script, or an HDL adapter directly.

Use core.fusion-api.rest-api-client for every read-only role, person, or worker lookup. That core skill owns the OAuth-backed REST client, REST version header, query encoding, pagination, retries, and response handling. Use core.data-loader for every upload, data-set initiation, import/load status, and diagnostics.

Cross-Pillar Catalog Scope

This Common skill is an HDL provisioning workflow, not a single FSM setup task. It intentionally has no singular task_code; record the User/UserRole business-object scope in its project artifacts rather than inventing a setup task identity.

Change scope and input assistance

Accept create, update and delete requests for User/UserRole records only when the live HDL business-object contract supports the requested operation. Removing a user-role assignment is not deletion of the role definition. Route custom-role creation, updates, deletion and redesign to Manage Job Roles or Manage Duties through common.security-console.

If users do not understand the HDL input, delegate sample/template generation to core.data-loader, explain its User/UserRole fields and map the requested values. Preserve unspecified fields and unrelated assignments. Use HDL metadata here; do not substitute an FSM CSV template or invent DELETE support.

Source preparation

Accept one readable HDL ZIP or plain-text User/UserRole DAT source.

SourceRequired action
Valid HDL ZIPPreserve its bytes exactly. Do not unzip, rezip, rename, or recreate it.
Valid DATCreate a separate staged ZIP and retain the original unchanged.
Repairable textNormalize UTF-8, remove a UTF-8 BOM, normalize LF line endings, and retain a DAT member name.
Corrupt ZIP or unrecoverable HDLStop before upload and state the exact correction required.

Validate User/UserRole metadata, record field counts, supported operations, and the required user and role keys. Do not invent, delete, merge, or alter user identifiers, role identifiers, or operations. Do not perform role membership, user existence, or User Roles list preflight.

Role and person resolution

When a source supplies a role display name instead of a role code, ask core.fusion-api.rest-api-client to retrieve the role metadata. Accept only one exact display-name match with a nonempty returned role code. For an exact set of matches, create a staged copy that changes only verified role identifier values and present the role-name-to-code mapping for user validation. For zero or multiple matches, present the resolved rows and ask the user for the intended role code.

When a required person number is absent, use core.fusion-api.rest-api-client to retrieve the person by exact username. If that response cannot provide a contract-valid person number, ask the same core client to perform the Workers fallback linked only by the verified Person ID. Accept one nonempty PersonNumber only when it belongs to that exact Person ID. Never substitute a Person ID, partial match, name, email, organization, or closest match for a PersonNumber. If no exact PersonNumber can be obtained, show the retrieved person details and ask the user to provide the number.

Never edit the supplied source in place. Keep staged files and identity responses transient. Do not persist user records, person identifiers, or user-to-role mappings in project artifacts.

Approval and core Data Loader handoff

Before import, confirm the target environment, source checksum, source validation, identifier-resolution result, file action, required privileges, and user validation of any staged conversion. Pass the validated immutable artifact to the core.data-loader session for validation and its final preview. The session owns execution approval, including its supported request-specific auto-approval behavior; do not request a separate approval before the handoff.

Core data-loader performs the dependent HDL upload and data-set initiation sequence, carries returned identifiers forward, and returns the accepted data load result. Retain only a redacted handoff with the environment, checksum, data-set name, Content ID, and Request ID.

On an explicit status, progress, result, count, or error request, pass the saved Request ID to core.data-loader and return its complete status report. Do not poll automatically, infer another request ID, or retry an import.

LDAP completion handoff

After core.data-loader reports a terminal successful load with no failed objects, prompt the user to run Send Pending LDAP Requests followed by Retrieve Latest LDAP Changes through common.security-console.user-security-common. That skill owns the ESS approval, active-instance check, submission, monitoring, and diagnostics.

Keep a redacted LDAP handoff containing each job name, returned ESS request ID, last status, and diagnostic reference. On a later explicit status request, route those saved identifiers to user-security-common; do not query or poll ESS directly.

The task is complete only when the HDL load and both LDAP jobs succeed. If a job is pending, timed out, failed, or not approved, report the task as incomplete. An explicit user completion override is recorded as manually overridden, not fully verified.

Failure behavior

  • Stop before side effects on invalid source, ambiguous identity resolution, missing privilege, missing approval, or inconsistent target environment.
  • Let core services classify authentication, transport, Fusion API, timeout, and process failures. Do not add a duplicate retry or polling loop.
  • Preserve redacted diagnostics and give the next corrective action.

Frequently asked questions

What does the Bulk User Role Provisioning AI skill do?

Prepares Oracle Fusion User/UserRole HDL sources, resolves missing role codes and person numbers through core REST services, and delegates approved HDL import, status, and LDAP follow-up to the owning core and Common-pillar skills.

Why use Bulk User Role Provisioning on TypingMind?

Because you install it once and use it with any model. Bulk User Role Provisioning 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 Bulk User Role Provisioning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oracle/Fusion-Setup-Configuration-Registry/tree/main/pillars/common/security-console/bulk-user-role-provisioning. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bulk User Role Provisioning?

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 Bulk User Role Provisioning?

As many as you like. As long as a model supports skills, you can use Bulk User Role Provisioning with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bulk User Role Provisioning 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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