dotfiles

Execute a planned multi-phase task — resume from /plan's committed artifacts and run each phase red→green→refactor inline in the main session under hook enforcement and script gates. Generation stays in one hot context; agents are spawned only to verify (spikes already done, review lanes, refuters, seam, provenance, drive). One final user gate over the whole task diff — for large tasks (15+ files), after /plan.

Archive an agreed design as a task specification — requirements with stable R-ids, a ratified tests.manifest.json (contract rows, decision rows with enforcement pointers, touch map, spike list), a slimmed mechanics doc for the prose residue, taste decisions drafted into meme, one tandem commit

Turn a ratified tests.manifest.json into an executable plan — scaffold phases, fill decision slots inline, run environment spikes as verification probes, lint, delta-review, bake baselines, and land one plan commit. The generation half of the build pipeline; everything it produces is a file, so /build resumes from disk. Run after /spec, before /build, for large multi-phase tasks.

Restore session context from the task checklist — add 'continue' to also resume execution from the first non-closed item

Code review via risk-routed judgment lanes — static tools first, then only the lanes the diff's surface warrants, blocker findings refuter-verified and fixed green-to-green

Dialectic architecture and design debate — argue until consensus, close every ambiguity, and land the agreement as falsifiable candidate rows (scenarios, decisions, spikes) ready for /spec to ratify

Close out a task — results generated from checklist and verification data plus a hand-written narrative delta, the amendment log drafted into meme, backlog reconciled, living docs swept for staleness

Write a teaching-grade, interactive learning report into ~/learning/ that distills what was worked on in the current conversation AND the related concepts behind it — both at full depth. Subagents author markdown in a typed-block convention (quiz and diagram code fences, skippable fenced divs, callout blockquotes, front-matter metadata); a bundled pandoc converter renders each file into a self-contained interactive HTML page with a TOC, validated multiple-choice quizzes with per-option feedback, HTML diagrams, and a computed reading-time footer. Splits a large or multi-concept report into a directory of numbered pieces with an index. Use when the user says "/learning-report", "write a learning report", "document what we learned", "turn this into a learning doc", or asks to teach-back the session. An optional arg focuses the report on a specific topic.

Shared vocabulary for designing deep modules — module, interface, depth, seam, adapter, leverage, locality, the deletion test. Use when designing or restructuring a module's interface, deciding where a seam goes, making code more testable or AI-navigable, or when another skill (brainstorm, drag-audit, review) needs the deep-module vocabulary.

Audit a codebase for "codebase drag" — the hidden overhead that makes every task take longer than it should. Scores five signals (Apology Estimate, Deploy Fear, Don't-Touch-That File, Coverage Lie, Time to First Commit) on a 0-10 scale using parallel sub-agents. Use this skill whenever the user asks about codebase health, engineering velocity, technical debt assessment, why the team is slow, code quality audit, or wants to measure how much friction their codebase creates. Also trigger when users mention "drag audit", "codebase drag", or reference the Piechowski article. A follow-up deepening scan turns high-scoring signals into concrete refactor candidates — trigger it directly when the user asks where the drag comes from, for "deepening opportunities", or to find shallow modules.

Diagnosis loop for hard bugs and performance regressions — feedback loop first, hypotheses second, fix behind a regression test. Use when the user says "diagnose"/"debug this", or reports something broken, throwing, failing, or slow.