python-gpt-po: AI-powered translator for gettext .po files using OpenAI, Azure OpenAI, Claude, DeepSeek and Ollama, supports

by pescheckit · Agent Tool · ★ 50

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install python-gpt-po

docker pull ghcr.io/pescheckit/python-gpt-po:latest
git clone https://github.com/pescheckit/python-gpt-po.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 71/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aianthropicautomationbatch-processingbulk-translatorclaudedeepseekgpti18nlanguage-translation

Quick Facts

Stars50
Forks17
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score71/100
Last Updated2026-03-03
Created2023-11-29
Platformsclaude-code, python
Est. Tokens~32k

About python-gpt-po

GPT-PO Translator Translate gettext (.po) files using AI models. Supports OpenAI, Azure OpenAI, Anthropic/Claude, and DeepSeek with automatic AI translation tagging and context-aware translations. 🚀 Quick Start ✨ Key Features Multiple AI providers - OpenAI, Azure OpenAI, Anthropic/Claude, DeepSeek, Ollama Context-aware translations - Automatically uses for better accuracy with ambiguous terms AI...

Compatible Skills

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  • Supervertaler-Workbench — semantic(0.32)+rare_topics+same_lang+similar_pop+shared_platform (55%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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