By zernie
Compile CLAUDE.md and AGENTS.md instruction files into typed .spec.ts files with compiler-grade guarantees, then lint, test, and enforce those specs using real linter rules from ESLint, Ruff, Clippy, and others.
Adopt a typed .spec.ts for an existing hand-written CLAUDE.md — start from the file you already have, non-destructively
Edit a vigiles .spec.ts to change a compiled instruction file (CLAUDE.md / AGENTS.md) — add, modify, or remove a rule, section, command, or key file. Use whenever you need to change a CLAUDE.md/AGENTS.md that carries a vigiles hash (edit the spec, never the artifact), including adding a new enforce()/check()/guidance() rule.
Deep linter reference for authoring or debugging a vigiles enforce() rule — plugin tables, AST selectors, type-aware rules, auto-fix, and edge cases for ESLint, Ruff, Pylint, RuboCop, and Stylelint. Use when you need the exact rule name or config for a specific linter, not for running a linter.
Upgrade a vigiles spec's guidance() rules to enforce() — scan the guidance rules in a CLAUDE.md/AGENTS.md spec and find existing linter rules (ESLint, Ruff, Clippy, Pylint, RuboCop, Stylelint) that back them. Use when asked to strengthen, harden, or make vigiles rules enforceable; NOT for general linting or fixing lint errors.
Install vigiles and test a Claude Code harness — hooks, skills, settings, CLAUDE.md — by picking the right tier (unit / deterministic / eval) and writing a test that passes. Use when the user wants to check that a hook fires or blocks, that a skill triggers, that injected context lands, or that a harness change moves what the agent does.
Modifies files
Hook triggers on file write and edit operations
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Make the harness your AI agent runs on reliable.
Agent = Model + Harness. The model gets the headlines — but the harness (your
CLAUDE.md, hooks, and skills) is the half you control, and it fails silently: a
stale reference, a guard that fails open, a skill that never fires. vigiles[^name]
makes it prove itself — verify, gate, test, measure — mostly free, no API key; the
real-model checks run on your Claude Pro/Max subscription, not metered tokens.
Four instruments, adopt any:
| 🔎 Lint | Your CLAUDE.md stops lying to the agent — every path, script, symbol & linter rule checked against reality, not just well-formed. → |
| 🛡 Guard | A safety hook that can't silently fail open — write it as a typed function, vigiles compiles a guard that actually blocks. → |
| 🧪 Test | Prove your hooks, skills & subagents actually do their job — free, no API key. → |
| 📊 Eval | Know if a skill helps or just costs — A/B on real tasks: the bill + correctness, on your own subscription. → |
Pick the one that hurts today. No TypeScript? vigiles lint + inline
<!-- vigiles:enforce --> comments work on any CLAUDE.md. Ship plugins?
vigiles scan ranks a marketplace by structural health, no key. Works with
Claude Code and Codex (vigiles/codex), or
teach it your own harness.
Paste into Claude Code or Codex:
Set up vigiles in this repo with good defaults (lint + test, non-interactive).
Verify my CLAUDE.md / AGENTS.md references and show me what's stale, then write
and run a harness test for one of my hooks or skills. Ask me first before gating
it in CI, adding a real-model eval, or enforcing strictly (--strict).
Or do it yourself:
npx vigiles init # sets up lint + test: spec + harness test + CI + plugin
Interactive in a terminal, non-interactive for agents/CI (or --yes).
You don't hand-write any of this — your agent does. init installs
model-invocable skills, so a plain-English ask does the work (it edits the source
and recompiles on save; you never touch it by hand):
npx claudepluginhub zernie/vigilesValidation and quality enforcement for Claude Agent SDK projects with TypeScript type checking and structure validation.
Self-audit AI agent, tool, and MCP-server code for security and reliability misconfigurations with Trustabl, the static analyzer for the OpenAI Agents SDK, Claude Agent SDK, Google ADK, and MCP. Ships two skills (trustabl-scan and trustabl-enrich) and a subagent (trustabl) that together form a scan → enrich → review → apply pipeline.
A CLI tool for validating AI coding agents
Audit CLAUDE.md files against Anthropic best practices
Check how well your repo supports AI coding agents.
Security controls for AI agents — deterministic policy enforcement, OWASP ASI10 scanning, and audit trails.