falsegreen-skill
v0.8.2LLM-based semantic analysis for false-positive test detection. Applies the J1-J6 judgment framework across Python, TypeScript, JavaScript, and Robot Framework, plus semantic patterns no static tool can see.
By Vinicius QueirozLicense: MIT1.1k GitHub starsUpdated 2 days ago
Directory evidence
- Runtimes
- Codex
- Parsed components
- 1 skill or MCP entry
- Source updated
- Sep 22, 2026
- Manifest status
- Canonical path parsed
The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →
Install falsegreen-skill for Codex
codex plugin marketplace add hashgraph-online/awesome-codex-plugins
codex plugin marketplace upgrade awesome-codex-plugins
codex plugin add falsegreen-skill@awesome-codex-pluginsPaste and run these commands in a terminal with Codex. They add and refresh the awesome-codex-plugins catalog, then install this plugin.
Compatibility: the page URL and API slug “falsegreen-skill” remain stable.
- Codex:
falsegreen-skill@agent-plugin-marketplace→falsegreen-skill@awesome-codex-plugins
The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.
Get the source manually
git clone https://github.com/hashgraph-online/awesome-codex-pluginsClone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is plugins/vinicq/falsegreen-skill/.
Plugin files
├── .codex-plugin/plugin.json└── skills/falsegreen-skill/SKILL.md
Included Skills1
Analyze test files for false-positive smells, meaning tests that pass even when the code breaks. Use when the user asks to review tests for false positives, weak assertions, mock misuse, test smells, or asks whether a test can actually fail. Covers Python (pytest, unittest), TypeScript, JavaScript (Jest, Vitest, Mocha), and Robot Framework.
Plugin manifests1
{
"name": "falsegreen-skill",
"version": "0.8.2",
"description": "LLM-based semantic analysis for false-positive test detection. Applies the J1-J6 judgment framework across Python, TypeScript, JavaScript, and Robot Framework, plus semantic patterns no static tool can see.",
"author": {
"name": "Vinicius Queiroz",
"url": "https://github.com/vinicq"
},
"homepage": "https://github.com/vinicq/falsegreen-skill",
"repository": "https://github.com/vinicq/falsegreen-skill",
"license": "MIT",
"skills": "./skills/",
"keywords": [
"testing",
"test-smells",
"code-quality",
"false-positive",
"python",
"typescript",
"javascript",
"robotframework"
],
"interface": {
"displayName": "falsegreen-skill",
"shortDescription": "Detect false-positive tests with the J1-J6 judgment framework",
"composerIcon": "./assets/icon.svg",
"logo": "./assets/icon.svg",
"developerName": "Vinicius Queiroz",
"capabilities": [
"Read",
"Write"
],
"websiteURL": "https://vinicq.github.io/falsegreen-docs/",
"privacyPolicyURL": "https://github.com/vinicq/falsegreen-skill/blob/master/PRIVACY.md",
"termsOfServiceURL": "https://github.com/vinicq/falsegreen-skill/blob/master/LICENSE",
"longDescription": "falsegreen-skill applies six structural judgments (J1-J6) to each test to determine whether it can actually fail when the code breaks. Covers the full falsegreen catalog for Python, TypeScript, JavaScript, and Robot Framework, plus semantic patterns only an LLM can detect. Provides HIGH/LOW confidence findings with evidence and fix hints.",
"category": "code-quality",
"defaultPrompt": [
"Analyze this test file for false-positive smells"
]
}
}For maintainers
If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.
[falsegreen-skill on Agent Plugins Marketplace](https://pluginsmp.com/plugins/falsegreen-skill)