Reikai

Investigate a non-trivial task before planning. Produces a findings report with file:line citations covering current behavior, upstream/reference equivalents, framework bridges, helpers to reuse, and open questions. Use before porting an upstream change, migrating a screen to Compose, touching unfamiliar modules, or any cross-cutting change. The point is to ground the plan in evidence, not memory.

Trim verbose prose, walls of text, journey narration, and WHAT comments from docs and code without losing vital info. Targets markdown files (docs, CLAUDE.md, rules, skills, agents) and, when asked, code comments / KDoc. Applies the "WHY not WHAT" rule, the "describe current behavior not the journey" rule, and the "release notes not implementation rationale" rule from `.claude/rules/workflow.md` and `.claude/rules/code-quality.md`. Use after a feature lands and the docs around it have accumulated cruft, or when a file feels heavier than it earns. Always plans before editing.

Find and fix a bug. Default is careful (reproduce, investigate, test). Add `--fast` for emergency production mode (hotfix branch, minimal change, ship a PR fast).

Audit a Reikai feature ported onto Mihon for behavioral parity against the Yōkai-era source on the `design/library-compose` branch. Use when the user asks to audit, verify, or sanity-check a ported feature, when they want to know whether a port "really matches" the original, or when they want a defect-fix pass on a recently-ported area. Takes a scope argument like "novel reader" or "Settings → Security". Compares features and behavior only, NOT pixels or layout (the user often redesigns visuals on the way over).

Scan changes, commit, push, and create a PR. With confirmation at each step

Deep, fan-out research over the codebase to answer a big question (test gaps, how a subsystem works end to end, a risk/security/dead-code audit, "where does X happen everywhere"). The codebase analog of deep web research: parallel explorer agents gather file:line-cited findings, surprising or high-stakes claims are adversarially verified against current code, and the result is a single prioritized report. Use for broad/deep questions that span many files and modules, NOT a one-file lookup and NOT a single-task pre-plan (use /scout for that, /explain for one thing).

Estimate per-turn token cost of this project's `.claude/` configuration and `CLAUDE.md`. Reports always-loaded vs path-scoped vs invoked-only, ranks the top contributors, and flags entries over budget. Add `--api` for exact counts via Anthropic's count_tokens endpoint instead of the chars/4 heuristic.

Review code changes or a pull request. Delegates to specialist agents for code quality, security, performance, and documentation, in parallel.

Safely refactor code with test coverage as a safety net

Set up dotclaude in any project end-to-end. Bootstrap `.claude/` from the bundled template if missing, then customize every config file to match the project's actual tech stack, conventions, and patterns.

Write comprehensive tests for new or changed code. Use automatically when new features are added, functions are created, or behavior is modified.