vindm
UserAI dev infrastructure framework for Claude Code. /dotclaude:bootstrap authors CLAUDE.md + docs/ + .claude/ tuned to your project. Per-domain: design (showpiece), coding, planning, testing, data, ai-workflow.
Categories
Indexed Skills (12)
migration-create
Author a database schema migration safely — one atomic change per migration, classified by risk with an explicit confirmation gate on destructive changes, access policies composed in the same migration as any new table, generated artifacts regenerated after, and a smoke test before declaring done. Discovers the project's own migration tool, conventions, and regen command at runtime. Use whenever you need to change the schema.
decomposition
Decompose a file that has grown over the size ceiling into focused sibling files — extracting at cognitive seams (hooks, sub-components, pure helpers, types), in the right order, behind a user-approved plan, with post-extraction verification. Invoke when a file-size check warns or a file has become too large to navigate. Refuses on auto-generated, snapshot, and fixture files.
knowledge-layers
The authority order across a project's three knowledge layers — guidance (.claude/), code (truth), and docs/ (reflection + transient intent) — with code as the tiebreak when a doc and the code disagree. Load when reading or trusting a doc to make a code decision, when authoring rules or skills that reference docs, or whenever a load-bearing fact comes from a description rather than from the code itself.
operating-discipline
Core operating discipline for any non-trivial task — understand before building, reason to the right solution, execute completely and verified, stay lean, and avoid the parallel-path and subagent-dispatch traps. Load this on any substantive coding, design, planning, debugging, refactor, or review work (skip only for pure mechanics like a typo or an explicit one-liner). The universal "how to work" base, consumed as-is.
element-reuse
Before reusing an existing string, component, or copy pattern on a NEW surface — locate its current usage with grep, classify both the existing and the proposed surface by type, and apply the verdict matrix. Catches first-touch copy leaking onto a daily-driver surface, a bug invisible to lint, code review, and per-surface visual review. Load at design time and audit time on any borrowed user-visible element.
iterative-polish-autoloop
Drive a multi-screen flow from raw to award-quality through a bounded iterative loop — reset to a clean fixture, capture every state, grade across three scrutiny layers (reviewer agent + composition scan + backend-truth probe), apply ONE highest-ROI fix, commit atomically, re-run — until award-quality OR a hard iteration cap. Invoke for iterative UI/UX polish on a flow with an auto-capture harness.
journey-mapping
Build the prior-surface inventory before designing OR auditing any screen — walk every surface the user touched before reaching this one, classify each by type, and apply the forbidden-pattern matrix so first-touch copy/voice/chrome never leaks onto a daily-driver surface. Load before any new design spec or any single-screen / flow audit.
persona-testing
Run three orthogonal outside-eyes tests on every user-visible string — day-30 (frequency-jaded), partner (voice-register), and stranger (already-knows-me) — to catch voice violations that pass a deny-list but still feel wrong. Load at design time on every proposed string and at audit time on every visible string on a captured surface.
ai-workflow
Set up LLM workflow discipline for projects that use AI / LLM calls in production or eval suites. Authors an eval-cost-watcher agent that projects token cost BEFORE regression evals run, plus an AI-workflow-discipline rule covering mock-mode placement, fixture freshness, and multi-stage cost accumulation. Optionally a small eval-regression skill stub. Invoke /dotclaude:ai-workflow only when the project actually has AI workflows.
data
Set up database / persistent-state discipline for a project with a DB. Authors a data-auditor agent (5 categories of integrity check), a migration-create skill, query-discipline rule (CLI > MCP DB tool for reads), and edit-time regen hook — all derived from the project's actual schema, migration framework, and access-control model. Optionally an RLS-security-reviewer if Postgres + row-level security is in use. Invoke /dotclaude:data in any project with persistent state.
worktree
Set up worktree-per-feature discipline for a project where several AI sessions (or humans + agents) work concurrently and collide in one checkout. Writes a thin `worktree:` config block that the plugin's CONSUMED main-checkout hook reads (no rendered per-project hook copy), plus a project-specific worktree lifecycle skill — calibrated by interview (which repo, what's exempt, how a fresh worktree gets configured) and PROVEN by a live smoke worktree before handoff. Invoke /dotclaude:worktree when parallel sessions are real or planned.
design
Elicit the project's design north-star + design-system reference (the two artifacts the consumed design audits read at runtime); no agent copies are authored. Derived from the project's actual UI surfaces, the user's named design benchmarks, and past design failure modes. Invoke /dotclaude:design in any project root that has a human-facing surface.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.