tether-ai: Tether Agent

by tt-11-dd · Codex Skill · ★ 92

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

How to install tether-ai

git clone https://github.com/tt-11-dd/tether-ai.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 65/100

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.

aagentaiclaude-codecodexharnesspi

Quick Facts

Stars92
Forks12
LanguageTypeScript
CategoryCodex Skill
LicenseMIT
Quality Score65/100
Open Issues1
Last Updated2026-10-09
Created2026-08-15
Platformsclaude-code, codex, node
Est. Tokens~15k

About tether-ai

Tether A local-first AI coding workbench built on the Pi ecosystem Let DeepSeek and OpenAI-compatible models inspect, edit, and verify your repositories with explicit safety boundaries. English · 简体中文 · Download latest Tether is an Electron desktop agent for real codebases.

Compatible Skills

These tools work well together with tether-ai for enhanced workflows:

  • pi-maestro-flow — semantic(0.41)+complementary+same_lang+similar_pop+shared_platform (64%)
  • agent-harness-generator — semantic(0.38)+complementary+same_lang+similar_pop+shared_platform (63%)
  • metaharness — semantic(0.38)+complementary+same_lang+similar_pop+shared_platform (63%)

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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:

View on GitHub → Browse Codex Skill tools