§ reference · skill
discover
Interviews you one question at a time to capture feature intent (Goals · Non-Goals · Functional Requirements · Acceptance Criteria · Decisions) into a Feature Requirements Document the research skill consumes.
§ 01 · purpose
Purpose
The canonical entry point when the feature idea is still fuzzy. discover pins down intent through a one-question-at-a-time interview so subsequent agents do not chase the wrong target. The FRD's Decisions block is consumed by research and propagates through Developer Context into design.
§ 02 · when to use
When to use it
- The idea is fuzzy and the team wants it stress-tested before any codebase probe.
- You have a half-written ticket or rough spec to refine into a structured FRD.
- Skip when you already have a clear spec or ticket — go straight to
research.
§ 03 · inputs
Inputs
| Name | Required | Source |
|---|---|---|
$ARGUMENTS | yes | Free-text feature description OR path to an existing FRD/ticket/doc to refine |
- $ARGUMENTS
- A path triggers refinement mode — file is read FULLY as baseline context.
§ 04 · outputs
Outputs
| Artifact | Path | Format |
|---|---|---|
| Feature Requirements Document | .rpiv/artifacts/discover/ | markdown (research-compatible) |
§ 05 · key steps
Key steps
- Foundational intent question first — no agents, no
file:lineWhy: Intent shapes the probe scope. Probing the codebase before stated intent risks framing the FRD around what exists rather than what the developer is trying to solve. - Lightweight codebase probe shaped by stated intent Why: Parallel locator agents run only after the intent answer narrows the slice. Keeps probe cost proportional to the feature size, not the codebase size.
- Build the decision tree lazily — root + immediate children Why: Expanding one layer at a time avoids speculative questions that depend on answers not yet given.
- Batch-confirm evidence-based pre-resolutions Why: When the probe surfaces a likely answer, the agent proposes it for confirmation rather than silently recording it. Surfaces disagreement before it propagates downstream.
- Interview loop — tiered questions, re-queue cross-cutting answers Why: Each answer can spawn follow-ups; cross-cutting answers re-queue affected branches so the tree stays internally consistent.
- Synthesize answers into FRD sections; write a fresh artifact Why: Each invocation always writes a NEW timestamp-distinct artifact — never appends — so a prior FRD is never silently mutated mid-iteration.
§ 06 · related skills