By zernie
Automate enforcement of coding standards by converting PR review comments into lint rules for ESLint, Ruff, RuboCop, and more across JS/TS, Python, Ruby, Rust; validate, upgrade, and generate typed .spec.ts from CLAUDE.md/AGENTS.md; audit repos for AI dev feedback loop maturity with CI/linter checks.
npx claudepluginhub zernie/vigilesScan the current repo and score its feedback loop maturity for AI-assisted development
Edit a vigiles spec file to update instruction files (CLAUDE.md, AGENTS.md)
Validate that all rules have proper enforcement classification (enforce/check/guidance)
Generate or iterate on the vigiles logo using ImageRouter API
Add a new enforce(), check(), or guidance() rule to an existing spec file
Convert an existing hand-written CLAUDE.md into a typed .spec.ts file for incremental adoption
Convert a recurring PR review comment into an automated lint rule with tests and spec entry
Upgrade guidance() rules to enforce() by finding existing linter rules that match
Deterministic linting hooks, semantic code validators, and a multi-LLM advisory council. Enforces coding rules mechanically — not by suggestion.
Documentation and authoring workflow router: audit docs vs code drift, sync docs after changes, optimize prompts and SKILL.md files, validate GLFM and Markdown formatting, summarize files/URLs/images with fidelity enforcement. Use when: docs are out of date, CLAUDE.md needs improving, SKILL.md needs optimizing, checking if documentation matches code, summarizing files or URLs.
LLM-powered guardrails for Claude Code. Turn every AI mistake into a rule AI can't repeat.
Check how well your repo supports AI coding agents.
OpenAI Codex MCP integration for Claude Code — audit, implement, verify, review, and debug via Codex
Modifies files
Hook triggers on file write and edit operations
Share bugs, ideas, or general feedback.
Efficient skill management system with progressive discovery — 410+ production-ready skills across 33+ domains
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