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 skills add malue-ai/dazee-small --skill local-file-encryptgit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/local-file-encrypt)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/local-file-encrypt"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/local-file-encrypt/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/skills/malue-ai/dazee-small/local-file-encrypt"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/local-file-encrypt.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 | $0.00029 | $0.00933 |
| Opus 5 | $0.00015 | $0.00466 |
| Sonnet 5 | $0.00006 | $0.00187 |
| Haiku 4.5 | $0.00003 | $0.00093 |
Grade A, and why
local-file-encrypt 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 9d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
本地文件加密
帮助用户加密和解密本地文件:使用 AES-256 强加密保护敏感文档,全程本地处理。
使用场景
- 用户说「帮我加密这个文件」「给这份合同加个密码」
- 用户说「解密这个文件」「打开加密的文档」
- 用户说「批量加密这个文件夹里的文件」
依赖安装
首次使用时自动安装:
pip install cryptography
执行方式
通过 Python 使用 cryptography 库实现 AES-256 加密。
加密文件
import os
from cryptography.fernet import Fernet
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
import base64
def derive_key(password: str, salt: bytes) -> bytes:
"""From password derive encryption key."""
kdf = PBKDF2HMAC(
algorithm=hashes.SHA256(),
length=32,
salt=salt,
iterations=480000,
)
return base64.urlsafe_b64encode(kdf.derive(password.encode()))
def encrypt_file(input_path: str, output_path: str, password: str):
"""Encrypt a file with password."""
salt = os.urandom(16)
key = derive_key(password, salt)
f = Fernet(key)
with open(input_path, 'rb') as file:
data = file.read()
encrypted = f.encrypt(data)
with open(output_path, 'wb') as file:
file.write(salt + encrypted) # salt prepended
print(f"Encrypted: {output_path} ({len(data)} -> {len(encrypted)+16} bytes)")
# Usage
encrypt_file("/path/to/secret.pdf", "/path/to/secret.pdf.enc", "user_password")
解密文件
def decrypt_file(input_path: str, output_path: str, password: str):
"""Decrypt a file with password."""
with open(input_path, 'rb') as file:
raw = file.read()
salt = raw[:16]
encrypted = raw[16:]
key = derive_key(password, salt)
f = Fernet(key)
decrypted = f.decrypt(encrypted)
with open(output_path, 'wb') as file:
file.write(decrypted)
print(f"Decrypted: {output_path} ({len(decrypted)} bytes)")
# Usage
decrypt_file("/path/to/secret.pdf.enc", "/path/to/secret.pdf", "user_password")
批量加密
import os
def encrypt_directory(dir_path: str, password: str):
"""Encrypt all files in a directory."""
encrypted_dir = dir_path + "_encrypted"
os.makedirs(encrypted_dir, exist_ok=True)
count = 0
for filename in os.listdir(dir_path):
filepath = os.path.join(dir_path, filename)
if os.path.isfile(filepath):
encrypt_file(filepath, os.path.join(encrypted_dir, filename + ".enc"), password)
count += 1
print(f"Encrypted {count} files -> {encrypted_dir}")
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.
- 9d ago First seen · 133 lines · 29 tokens per session scan A 91ef4127eeae
local-file-encrypt is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 933 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.
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