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Set up the DataOps issue-driven role-agent process so work in DataTalksClub/dataops can move from raw intake through grooming, implementation, testing, acceptance, merge, and CI/deploy monitoring.
This includes documenting the repo-specific workflow, creating role-agent instructions for Product Manager, Architect, Process Curator, Assistant Engineer, Software Engineer, Tester, and On-Call Engineer, and ensuring GitHub labels match the pipeline described in _docs/PROCESS.md.
The setup should align with _docs/MERGE_PLAN.md Phase 0 and support the first merge-track issues for importing DTC Operations and keeping the docs app running from the merged repo.
Acceptance Criteria
_docs/PROCESS.md clearly defines the DataOps issue lifecycle, mandatory gates, role responsibilities, issue format, label taxonomy, merge rules, testing expectations, and human-verification handling.
Role-agent instruction files exist for Product Manager, Architect, Process Curator, Assistant Engineer, Software Engineer, Tester, and On-Call Engineer, with repo-specific responsibilities and handoff rules.
Role-agent instructions require agents to read _docs/PROCESS.md before issue work and to respect the source-repo boundary for ../dtc-operations, ../datatasks, and ../podcast-assistant.
GitHub labels needed by _docs/PROCESS.md exist in DataTalksClub/dataops, including workflow, type, area, and priority labels.
Initial merge-track issues are filed or confirmed for Phase 0/Phase 1 work, with raw issues carrying needs grooming until the Product Manager grooms them.
A role agent can inspect an issue and determine the next owner, required gates, dependencies, and expected verification steps without relying on chat context.
Test Scenarios
Scenario: Product Manager grooms a raw issue
Given: a raw GitHub issue with the needs grooming label
When: the Product Manager role agent follows the documented process
Then: the issue is rewritten into the groomed format, receives appropriate labels, records dependencies, and no longer has needs grooming
Scenario: Software Engineer starts implementation after grooming
Given: a groomed implementation issue with dependencies and acceptance criteria
When: the Software Engineer role agent starts work
Then: the agent can identify scope, out-of-scope items, required tests, commit expectations, and handoff requirements from the issue and process docs
Scenario: Merge and deploy monitoring follow the pipeline
Given: an implemented issue that passed tester and Product Manager acceptance
When: the orchestrator merges and pushes the approved branch
Then: the On-Call Engineer role agent knows to monitor CI/deploy status and report or fix failures according to the documented process
Out of Scope
Importing code or content from ../dtc-operations, ../datatasks, or ../podcast-assistant.
Implementing portal, backend, frontend, assistant, or work-engine functionality.
Refactoring the source repositories.
Replacing local merge workflow with pull requests unless separately requested.
Set up role-agent process for DataOps
Status: pending
Tags:
docs,process-docs,P0Depends on: None
Blocks: #2, #3
Scope
Set up the DataOps issue-driven role-agent process so work in
DataTalksClub/dataopscan move from raw intake through grooming, implementation, testing, acceptance, merge, and CI/deploy monitoring.This includes documenting the repo-specific workflow, creating role-agent instructions for Product Manager, Architect, Process Curator, Assistant Engineer, Software Engineer, Tester, and On-Call Engineer, and ensuring GitHub labels match the pipeline described in
_docs/PROCESS.md.The setup should align with
_docs/MERGE_PLAN.mdPhase 0 and support the first merge-track issues for importing DTC Operations and keeping the docs app running from the merged repo.Acceptance Criteria
_docs/PROCESS.mdclearly defines the DataOps issue lifecycle, mandatory gates, role responsibilities, issue format, label taxonomy, merge rules, testing expectations, and human-verification handling._docs/PROCESS.mdbefore issue work and to respect the source-repo boundary for../dtc-operations,../datatasks, and../podcast-assistant._docs/PROCESS.mdexist inDataTalksClub/dataops, including workflow, type, area, and priority labels.needs groominguntil the Product Manager grooms them.Test Scenarios
Scenario: Product Manager grooms a raw issue
Given: a raw GitHub issue with the
needs groominglabelWhen: the Product Manager role agent follows the documented process
Then: the issue is rewritten into the groomed format, receives appropriate labels, records dependencies, and no longer has
needs groomingScenario: Software Engineer starts implementation after grooming
Given: a groomed implementation issue with dependencies and acceptance criteria
When: the Software Engineer role agent starts work
Then: the agent can identify scope, out-of-scope items, required tests, commit expectations, and handoff requirements from the issue and process docs
Scenario: Merge and deploy monitoring follow the pipeline
Given: an implemented issue that passed tester and Product Manager acceptance
When: the orchestrator merges and pushes the approved branch
Then: the On-Call Engineer role agent knows to monitor CI/deploy status and report or fix failures according to the documented process
Out of Scope
../dtc-operations,../datatasks, or../podcast-assistant.