opencode-fusion: Main agent plans and reviews; cheaper sidekick edits. Devin Fusion pattern for OpenCode

by mihneaptu · Codex Skill · ★ 216

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How to install opencode-fusion

npx skills add mihneaptu/opencode-fusion --skill fusion-setup -g -a opencode -y

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.

ai-agentsai-codingclaude-codecodexcoding-agentsdevin-fusionfusionmodel-routingmulti-agentopencode

Quick Facts

Stars216
Forks13
LanguageJavaScript
CategoryCodex Skill
LicenseMIT
Quality Score71/100
Last Updated2026-08-24
Created2026-06-30
Platformsclaude-code, codex, node
Est. Tokens~20k

About opencode-fusion

opencode-fusion A minimal, working multi-model team for opencode: a main agent that plans and reviews but cannot edit files, delegating every change to a cheaper, faster sidekick. Inspired by the Devin Fusion "sidekick" pattern from Cognition. The main agent's file editing is mechanically denied - its only way to change a file is to hand a spec to the sidekick.

Compatible Skills

These tools work well together with opencode-fusion for enhanced workflows:

  • devin-handoff — semantic(0.36)+complementary+similar_pop+shared_platform (53%)
  • ClaudeCodeExtension — semantic(0.29)+complementary+similar_pop+shared_platform (50%)
  • cligate — semantic(0.16)+complementary+rare_topics+similar_pop+shared_platform (50%)

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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