Locates files, directories, and components relevant to a feature or task. Call codebase-locator with human language prompt describing what you're looking for. Basically a "Super grep/find/ls tool" — Use it if you find yourself desiring to use one of these tools more than once.
You are a specialist at finding code patterns and examples in the codebase. Your job is to locate similar implementations that can serve as templates or inspiration for new work.
Finds what connects to a given component or area — inbound references, outbound dependencies, config registrations, event subscriptions. The reverse-reference counterpart to codebase-locator. Use when you need to understand what calls, depends on, or wires into a component.
Finds similar past changes in git history — commits, blast radius, follow-up fixes, and lessons from related thoughts/ docs. Use when planning a change and you need to know what went wrong last time something similar was done.
Finds existing manual test cases in .rpiv/test-cases/ — catalogs by module, extracts frontmatter metadata (id, priority, status, tags), and reports coverage stats. Use before generating test cases to avoid duplicates, or to audit what test coverage already exists in a project.
Discovers relevant documents in thoughts/ directory (We use this for all sorts of metadata storage!). This is really only relevant/needed when you're in a reseaching mood and need to figure out if we have random thoughts written down that are relevant to your current research task. Based on the name, I imagine you can…
Do you find yourself desiring information that you don't quite feel well-trained (confident) on? Information that is modern and potentially only discoverable on the web? Use the web-search-researcher subagenttype today to find any and all answers to your questions! It will research deeply to figure out and attempt to…
Generate architecture.md guidance files in .rpiv/guidance/ by analyzing architecture and patterns in parallel. Auto-detects architecture, proposes locations, and batch-writes compact documentation. Use for onboarding or improving AI assistant context.
Generate CLAUDE.md files across a project by analyzing architecture and patterns in parallel. Auto-detects architecture, proposes locations, and batch-writes compact documentation. Use for onboarding or improving AI assistant context.
Conduct comprehensive code reviews by analyzing changes in parallel. Produces review documents in thoughts/shared/reviews/. Use when changes are ready for review.
Create context-preserving handoff documents for session transitions. Compacts essential context into concise documents. Use when context is getting large or before starting a fresh session.
Design features through iterative vertical-slice decomposition and progressive code generation with developer micro-checkpoints. For complex multi-component features touching 6+ files across multiple layers. Produces design artifacts in thoughts/shared/designs/. Always requires a research artifact from discover →…
Generate trace-quality research questions from codebase discovery. Spawns discovery agents and reads key files for depth, then synthesizes into dense question paragraphs for the research skill. Produces question artifacts in thoughts/shared/questions/. First stage of the research pipeline.
Analyze solution options for features or changes. Compares approaches with pros/cons and provides recommendations. Produces documents in thoughts/shared/solutions/. Use when multiple valid approaches exist.
Execute approved implementation plans phase by phase. Implements changes with verification against success criteria. Use when a plan is ready for implementation.
Migrate existing CLAUDE.md files to .rpiv/guidance/ system. Finds all CLAUDE.md files, transforms references, and creates architecture.md files in the guidance shadow tree.
Discover testable features via Frontend-First Discovery and create a folder outline under .rpiv/test-cases/ with per-feature metadata. Incremental runs use existing outlines as context for smarter discovery and diff-based checkpoints. Use before write-test-cases to map project scope.
Create phased implementation plans from design artifacts. Decomposes designs into parallelized atomic phases with success criteria in thoughts/shared/plans/. Use after design.
Answer structured research questions via targeted parallel analysis agents. Consumes question artifacts from discover. Produces research documents in thoughts/shared/research/. Second stage of the research pipeline — always requires a questions artifact.
Resume work from a handoff document. Reads handoff, verifies current state, and continues implementation. Use at the start of a new session to pick up where you left off.
Update existing implementation plans based on feedback. Makes surgical edits while preserving structure and quality. Use when plans need adjustments after review or during implementation.
Verify that an implementation plan was correctly executed. Runs success criteria checks and generates validation reports. Use after implementation is complete.