rfe-creator¶
A comprehensive Claude Code skill suite for the full lifecycle of Requests for Enhancement (RFEs) in the RHAIRFE Jira project. Covers creation from problem statements, rubric-based review with auto-revision, intelligent splitting of oversized RFEs, and submission to Jira. Also provides strategy document skills (RHAISTRAT) for refining approved RFEs into implementation strategies with adversarial multi-reviewer validation.
The plugin uses a shared artifact convention -- all skills read from and write to
an artifacts/ directory with YAML frontmatter for structured metadata. Jira
write operations use deterministic Python scripts rather than LLM tool-calling,
while read operations support both Atlassian MCP and REST API fallback. A
dependency on the assess-rfe plugin provides the scoring rubric, bootstrapped
automatically on first use.
Plugin Details
- Version: 0.1.0
- Author: jwforres
- Category: Product Planning
- Repository: opendatahub-io/rfe-creator
- Tags: rfe jira review strategy pipeline
Pipeline¶
Dependencies¶
Skills¶
| Skill | Description | Invocable |
|---|---|---|
/rfe.create |
Generate new RFEs from problem statements | |
/rfe.review |
Score and improve RFEs with auto-revision | |
/rfe.split |
Decompose oversized RFEs into appropriately-scoped pieces | |
/rfe.submit |
Push RFEs to Jira | |
/rfe.speedrun |
Execute the full RFE pipeline end-to-end | |
/rfe.auto-fix |
Batch review, revise, and split operations | |
/strat.create |
Create strategy documents | |
/strat.refine |
Refine strategy documents | |
/strat.review |
Review strategy documents | |
/strat.prioritize |
Prioritize strategy items | |
/rfe-creator.update-deps |
Update vendored dependencies | |
/architecture-review |
Architecture review skill | |
/feasibility-review |
Feasibility review skill | |
/rfe-feasibility-review |
RFE feasibility review | |
/scope-review |
Scope review skill | |
/testability-review |
Testability review skill |
Installation¶
/plugin install rfe-creator@opendatahub-skills
Architecture¶
Two skill families: RFE skills (rfe.) for the requirements pipeline and Strategy skills (strat.) for implementation planning. A speedrun skill orchestrates the full end-to-end flow by invoking other skills.
Review skills use a forked reviewer pattern -- independent sub-agents (feasibility, testability, scope, architecture) run in isolated contexts and produce separate assessments that are synthesized into a consolidated review. The rfe.review skill is the central orchestrator: it launches parallel waves of fetch, assess, feasibility, review, and revise agents, polling for completion via scripts/check_review_progress.py.
State persistence uses scripts/state.py for long-running operations across context compression boundaries, and scripts/frontmatter.py manages YAML frontmatter on all artifact files. The rfe.auto-fix skill wraps this into a pipeline state machine (scripts/pipeline_state.py) that handles batching, resumption, and multi-phase dispatch with launch_wave/wait-for-wave synchronization.
Architecture context is fetched from opendatahub-io/architecture-context into .context/architecture-context/ and used by review and strategy skills to ground assessments in actual platform components and APIs.