opencode-gpt-imagegen: OpenCode plugin: image generation via your ChatGPT subscription

by yuji-hatakeyama · Codex Skill · ★ 109

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

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. Full audit →

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-agentschatgptcodexgpt-image-2image-generationopenaiopencodeopencode-plugintext-to-image

Quick Facts

Stars109
Forks23
LanguageTypeScript
CategoryCodex Skill
LicenseMIT
Quality Score67/100
Open Issues9
Last Updated2026-10-22
Created2026-05-13
Platformscodex, node
Est. Tokens~15k

About opencode-gpt-imagegen

opencode-gpt-imagegen Bring ChatGPT Images 2.0 () to OpenCode. Use it through your ChatGPT subscription (no API costs!) or through the OpenAI API — your call. Highlights Subscription-friendly. Generations ride on the same Codex backend channel OpenCode already uses for ChatGPT subscription chat — billed against your ChatGPT plan, not your API credits. Reference images.

Compatible Skills

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

  • mcp-image — semantic(0.43)+complementary+shared_fw(openai)+rare_topics+same_lang+similar_pop+shared_platform (77%)
  • gpt-image-2-mcp — semantic(0.56)+complementary+rare_topics+same_lang+similar_pop+shared_platform (74%)

opencode-gpt-imagegen alternative? Top 6 similar tools

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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