invincat: A native Python agent CLI built on DeepAgents CLI, featuring an independent memory Agent

by dog-qiuqiu · Codex Skill · ★ 117

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

How to install invincat

pip install invincat-cli
git clone https://github.com/dog-qiuqiu/invincat.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 67/100

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.

agentagent-skillsagentic-aiagentic-workflowaiautonomous-agentsclaude-codeclicodecode-generation

Quick Facts

Stars117
Forks9
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score67/100
Last Updated2026-05-26
Created2026-04-16
Platformsclaude-code, cli, codex, gemini, python
Est. Tokens~933k

About invincat

Invincat Invincat is a terminal-native AI coding assistant for local repositories. It can inspect and edit files, run shell commands with approval, use web/MCP tools, keep long-term memory, plan before execution, run scheduled tasks, and bridge remote WeCom messages into a project session. Features Work directly from your project directory in a terminal UI.

Compatible Skills

These tools work well together with invincat for enhanced workflows:

  • NanoCoder — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)
  • unoplat-code-confluence — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • cursor-agent — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)
  • superagentx — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)
  • boss-agent-cli — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)

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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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