Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/GoogilyBoogily/googilyboogily-claude-power-toolsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/googilyboogily/googilyboogily-claude-power-tools/validate-and-fix)<a href="https://agentmods.dev/commands/googilyboogily/googilyboogily-claude-power-tools/validate-and-fix"><img src="https://agentmods.dev/badge/commands/googilyboogily/googilyboogily-claude-power-tools/validate-and-fix/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/googilyboogily/googilyboogily-claude-power-tools/validate-and-fix"><img src="https://agentmods.dev/badge/commands/googilyboogily/googilyboogily-claude-power-tools/validate-and-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00010 | $0.01030 |
| Opus 5 | $0.00005 | $0.00515 |
| Sonnet 5 | $0.00002 | $0.00206 |
| Haiku 4.5 | $0.00001 | $0.00103 |
Grade A, and why
validate-and-fix scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Validate and Fix
Run quality checks and automatically fix discovered issues using parallel execution.
Process
1. SYSTEMATIC PRIORITY-BASED ANALYSIS
Command Discovery
First, discover what validation commands are available:
- Check AGENTS.md/CLAUDE.md for documented build/test/lint commands
- Examine package.json scripts section for available commands
- Look for common patterns in scripts:
- Linting: "lint", "eslint", "lint:fix", "check:lint", "lint:js"
- Type checking: "typecheck", "type-check", "tsc", "check:types", "types"
- Testing: "test", "test:unit", "jest", "check:test", "test:all"
- Formatting: "format", "prettier", "fmt", "format:fix"
- Build: "build", "compile", "build:prod"
- Check README.md for any additional validation instructions
Discovery with Immediate Categorization
Run all discovered quality checks in parallel using Bash. Capture full output including file paths, line numbers, and error messages:
- Linting (ESLint, Prettier, Ruff, etc.)
- Type checking (TypeScript, mypy, etc.)
- Tests (Jest, pytest, go test, etc.)
- Build verification
- Custom project checks
Immediately categorize findings by:
- CRITICAL: Security issues, breaking changes, data loss risk
- HIGH: Functionality bugs, test failures, build breaks
- MEDIUM: Code quality, style violations, documentation gaps
- LOW: Formatting, minor optimizations
Risk Assessment Before Action
- Identify "quick wins" vs. complex fixes
- Map dependencies between issues (fix A before B)
- Flag issues that require manual intervention
2. STRATEGIC FIX EXECUTION
Phase 1 - Safe Quick Wins
- Start with LOW and MEDIUM priority fixes that can't break anything
- Verify each fix immediately before proceeding
Phase 2 - Functionality Fixes
- Address HIGH priority issues one at a time
- Run tests after each fix to ensure no regressions
Phase 3 - Critical Issues
- Handle CRITICAL issues with explicit user confirmation
- Provide detailed plan before executing
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 110 lines · 10 tokens per session scan A ed5c458f9214
validate-and-fix is a command published in the GitHub repository GoogilyBoogily/googilyboogily-claude-power-tools (2 stars, last pushed 4mo ago), licensed MIT. It adds 10 tokens to every session and 1,030 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
cleanup
Systematically clean up code, remove dead code, and optimize project structure.
debug
Systematic debug loop: root cause before any fix. Four phases, an evidence ledger, the 3-fix architecture wall.
fix-ci
Start an iterative CI fix session — resolve the input (build / PR / branch / cwd), then run the fixing-ci skill loop until CI is green or you've hit the iteration cap.
fact-check-code
Verify claims about the codebase by searching code and optionally the web.
troubleshoot
Diagnose root cause of a bug/issue (investigation only, no code changes).
null-as-error
Invoke the null-as-error skill to audit the current project for silent error swallowing in Effect code.