Borrowing it
Nothing to install: this file belongs to bigmanBass666/wiztree-mcp. 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/bigmanBass666/wiztree-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/bigmanBass666/wiztree-mcpWrote 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/bigmanbass666/wiztree-mcp/agents-md)<a href="https://agentmods.dev/instructions/bigmanbass666/wiztree-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/bigmanbass666/wiztree-mcp/agents-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/bigmanbass666/wiztree-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/bigmanbass666/wiztree-mcp/agents-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 | $0.00856 | $0.00856 |
| Opus 5 | $0.00428 | $0.00428 |
| Sonnet 5 | $0.00171 | $0.00171 |
| Haiku 4.5 | $0.00086 | $0.00086 |
Grade A, and why
wiztree-mcp AGENTS.md scanned grade A with 1 finding 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- WizTree64.exe is a GUI app on Windows; `subprocess.run()` with `STARTUPINFO` hides its window. How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
wiztree-mcp
WizTree-based disk analysis MCP server. Scan drives, query disk usage, search paths, compare scans, and visualize file system data — all from Claude Code.
Quick Start
pip install wiztree-mcp
# WizTree64.exe required on Windows — install from https://diskanalyzer.com/
Register in .mcp.json:
{
"mcpServers": {
"wiztree": {
"type": "stdio",
"command": ".venv\\Scripts\\python",
"args": ["-m", "wiztree_mcp"]
}
}
}
Architecture
src/wiztree_mcp/
├── __init__.py
├── __main__.py # Entry point: from server import main; main()
├── server.py # FastMCP instance, lifespan, tool registration
├── database.py # SQLite CRUD (scans + entries tables)
├── models.py # Dataclasses (Scan, Entry, ScanType, EntryType)
├── csv_importer.py # CSV parser → bulk INSERT into SQLite
├── wiztree_cli.py # WizTree64.exe discovery & invocation
└── tools/
├── scan.py # scan_disk — primary data ingestion
├── query.py # disk_summary, top_entries, search_paths, drill_down
├── analysis.py # file_type_summary, large_old_files
├── compare.py # compare_scans — SQL FULL OUTER JOIN
└── manage.py # list_scans, get_treemap, cleanup_scans
Tools (11 total)
Data Ingestion
scan_disk(target, label?, max_depth?, export_folders?, export_files?, treemap?, timeout?)— Scan with WizTree, import CSV into SQLite
Query
disk_summary(scan_id, top_n?)— Drive info + capacity + top files/folderstop_entries(scan_id, kind?, limit?, offset?)— Largest files/folderssearch_paths(scan_id, query, kind?, limit?)— Keyword searchdrill_down(scan_id, folder_path, limit?, offset?)— Browse folder contentsfile_type_summary(scan_id, limit?)— Disk usage by extensionlarge_old_files(scan_id, older_than_days?, min_size_mb?, limit?)— Cleanup candidates
Comparison
compare_scans(scan_id_before, scan_id_after, limit?)— SQL JOIN diff
Management
list_scans()— Available scansget_treemap(scan_id)— PNG treemap imagecleanup_scans(keep_latest?)— Remove old scans
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 · 89 lines · 856 tokens per session scan A 9fe55a9f2d40
wiztree-mcp AGENTS.md is an instructions file published in the GitHub repository bigmanBass666/wiztree-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 856 tokens to every session, about $0.0043 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.