Borrowing it
Nothing to install: this file belongs to benseverndev-oss/goldencheck. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/benseverndev-oss/goldencheck/main/CLAUDE.mdgit clone --depth 1 https://github.com/benseverndev-oss/goldencheckWrote 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/instructions/benseverndev-oss/goldencheck/claude-md)<a href="https://agentmods.dev/instructions/benseverndev-oss/goldencheck/claude-md"><img src="https://agentmods.dev/badge/instructions/benseverndev-oss/goldencheck/claude-md/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/instructions/benseverndev-oss/goldencheck/claude-md"><img src="https://agentmods.dev/badge/instructions/benseverndev-oss/goldencheck/claude-md.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 | $0.02969 | $0.02969 |
| Opus 5 | $0.01484 | $0.01484 |
| Sonnet 5 | $0.00594 | $0.00594 |
| Haiku 4.5 | $0.00297 | $0.00297 |
Grade A, and why
goldencheck CLAUDE.md 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 8d 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GoldenCheck
Data validation that discovers rules from your data. DQBench Score: 88.40.
Commands
pip install -e ".[dev]" # Dev install
pip install -e ".[llm]" # With LLM boost
pip install -e ".[mcp]" # With MCP server
pip install -e ".[baseline]" # With deep profiling baseline
goldencheck baseline data.csv # Create statistical baseline
goldencheck scan data.csv --baseline goldencheck_baseline.yaml # Drift detection
pytest --tb=short -v # Run tests (189+ passing)
ruff check . # Lint
ruff check . --fix # Auto-fix lint
goldencheck data.csv --no-tui # Scan a file (CLI output)
goldencheck data.csv # Scan with TUI
goldencheck validate data.csv # Validate against goldencheck.yml
goldencheck diff old.csv new.csv # Compare two files
goldencheck fix data.csv # Auto-fix (safe mode)
goldencheck watch data/ # Poll directory for changes
goldencheck scan data.csv --domain healthcare # Domain-specific types
Architecture
goldencheck/
├── cli/ # Typer CLI (15 commands incl. baseline, scan, validate, review, diff, watch, fix, learn, mcp-serve)
├── engine/ # Scanner, validator, confidence, fixer, differ, watcher
├── profilers/ # 10 column profilers (BaseProfiler ABC)
├── baseline/ # Deep profiling: statistical, constraints, semantic, correlation, patterns, priors
├── drift/ # Drift detector (13 check types against saved baseline)
├── relations/ # Cross-column profilers (temporal, null correlation, numeric cross, age validation)
├── semantic/ # Type classifier + suppression engine + domain packs (healthcare, finance, ecommerce)
├── llm/ # LLM boost (providers, prompts, merger, budget, rule generator)
├── mcp/ # MCP server (9 tools incl. domain discovery)
├── config/ # Pydantic YAML config (goldencheck.yml)
├── models/ # Finding (with metadata dict), Profile dataclasses
├── notebook.py # ScanResult wrapper + HTML renderers for Jupyter/Colab
├── reporters/ # Rich, JSON, CI output
└── tui/ # Textual TUI (4 tabs)
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.
- 8d ago First seen · 228 lines · 2,969 tokens per session scan A 08065f157fc6
goldencheck CLAUDE.md is an instructions file published in the GitHub repository benseverndev-oss/goldencheck (2 stars, last pushed 4mo ago), licensed MIT. It adds 2,969 tokens to every session, about $0.0148 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.
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