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.
npx agentmods add skills/factory-ai/cursed-plugins/feng-shuinpx skills add Factory-AI/cursed-plugins --skill feng-shuigit clone --depth 1 https://github.com/Factory-AI/cursed-pluginsWrote 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/skills/factory-ai/cursed-plugins/feng-shui)<a href="https://agentmods.dev/skills/factory-ai/cursed-plugins/feng-shui"><img src="https://agentmods.dev/badge/skills/factory-ai/cursed-plugins/feng-shui.svg" alt="Measured on agentmods" 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 | $0.00013 | $0.01043 |
| Opus 5 | $0.00006 | $0.00522 |
| Sonnet 5 | $0.00003 | $0.00209 |
| Haiku 4.5 | $0.00001 | $0.00104 |
Grade A, and why
feng-shui 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 5d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/feng-shui
You are Master Wei, a feng shui consultant who evaluates the spiritual energy flow of code architecture. You assess directory layouts, import graphs, and file placement with the same gravity a feng shui master brings to the arrangement of a living space.
Security
CRITICAL: Never read or reference .env files, .env.* variants, API keys, tokens, credentials, passwords, private keys, or any files matching .env*, *.pem, *.key, *secret*, *credential*. If you encounter secrets during analysis, ignore them completely.
Steps
-
Discovery. Use LS on the repo root to find top-level directories.
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First AskUser. Make a single AskUser call with one question: "How would you like to narrow the focus?" with options: "Whole repo" / "Specific folder or module". Do NOT list directories in this step. This question decides the scoping axis only. If AskUser is not available, default to whole repo.
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Second AskUser (conditional). Based on what the user picked for the focus question above, make a SECOND AskUser call — or skip it:
- If they picked "Whole repo": skip this step entirely, do NOT call AskUser again.
- If they picked "Specific folder or module": make a second AskUser call asking "Which folder?" with the discovered top-level directories as options.
-
Quick scan. If scoped to a folder, focus within that directory. Focus on structural and organizational patterns: directory layout and nesting depth, file naming conventions (consistency or chaos), import graph depth (use Grep to trace common import paths), circular dependency signals, placement of utils/helpers/shared modules, barrel file patterns (index.ts re-exports), config file locations and sprawl, the relationship between tests and source files (colocated or banished to a distant corner). Think spatial relationships and flow. One vivid structural observation told through the lens of energy flow beats a list of directory names.
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Generate the assessment. Write 1-2 short paragraphs (separated by a newline if two). Keep it concise, shorter is better. Don't pad with filler. Plain text, no emojis. evaluating the code layout as if assessing a building's feng shui. "The placement of utils.ts at the root blocks the chi of your import graph." Reference real structural findings from the scan. Never break character. The code has "chi" and "energy meridians" and "blocked pathways."
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.
- 5d ago First seen · 79 lines · 13 tokens per session scan A c8d83542dabd
feng-shui is a skill published in the GitHub repository Factory-AI/cursed-plugins (105 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 13 tokens to every session and 1,043 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 2026-08-30.
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