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opencode-cli

84
B

This skill should be used when configuring or using the OpenCode CLI for headless LLM automation. Use when the user asks to "configure opencode", "use opencode cli", "set up opencode", "opencode run command", "opencode model selection", "opencode providers", "opencode vertex ai", "opencode mcp servers", "opencode ollama", "opencode local models", "opencode deepseek", "opencode kimi", "opencode mistral", "fallback cli tool", or "headless llm cli". Covers command syntax, provider configuration,...

#Claude CLI#CLI#OpenCode#OpenCode CLI#Environment Variables#headless LLM#local models#vertex
Also in: machine learning json testing

Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

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skilz install SpillwaveSolutions/opencode_cli/opencode-cli
skilz install SpillwaveSolutions/opencode_cli/opencode-cli --agent opencode
skilz install SpillwaveSolutions/opencode_cli/opencode-cli --agent codex
skilz install SpillwaveSolutions/opencode_cli/opencode-cli --agent gemini

First time? Install Skilz: pip install skilz

Works with 14 AI coding assistants

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

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Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/SpillwaveSolutions/opencode_cli
2. Copy the agent skill directory:
cp -r opencode_cli ~/.claude/skills/
View on GitHub

Need detailed installation help? Check our platform-specific guides:

Claude Desktop Guide Claude Code Guide Troubleshooting

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Agentic Skill Details

Owner
SpillwaveSolutions (GitHub)
Repository
opencode_cli
Type
Technical
Meta-Domain
cloud infrastructure
Primary Domain
terraform
Market Score
84
Agentic Skill Grades →

Agent Skill Grade

B
Score: 84/100 Click to see breakdown

Score Breakdown

Spec Compliance
13/15
PDA Architecture
27/30
Ease of Use
22/25
Writing Style
8/10
Utility
17/20
Modifiers: -3

Areas to Improve

  • Reference files lack TOCs
  • Vertex AI duplication
  • Second-person voice slips

Recommendations

  • Add trigger phrases to description for discoverability
  • Add table of contents for files over 100 lines

Graded: 2026-01-19

Developer Feedback

I took a look at your opencode_cli skill and wanted to share some thoughts.

Links:

The TL;DR

You're at 84/100, solidly in B territory. This is based on Anthropic's skill best practices rubric. Your strongest area is Progressive Disclosure Architecture (27/30) — the skill is well-structured with focused reference files that don't bloat the main file. Weakest spot is Utility (17/20) — the skill solves a real problem, but the feedback loops and error handling could be tighter.

What's Working Well

  • Progressive Disclosure is chef's kiss. You've got 6 focused reference files that delegate responsibility perfectly. SKILL.md stays lean at 195 lines while each reference goes exactly one level deep. That's the right structure.
  • Discovery-friendly. Your trigger phrases are solid — "configure opencode", "vertex ai", "mcp servers", "ollama", "local models" — these will actually get Claude to activate the skill when people ask about that stuff.
  • Token economy. Minimal redundancy in the main file. You're not repeating yourself across sections, which keeps things efficient.
  • Practical examples. The JSON config templates and Python subprocess integration patterns give people real, copy-paste-ready code to work with.

The Big One: Reference Files Need Navigation

Your reference files are 200-380 lines but they're missing tables of contents. cloud-providers.md (351 lines), integration-patterns.md (217 lines) — when someone lands in these files looking for a specific provider or pattern, they're scrolling blind.

The fix: Add a ## Table of Contents section at the top of each reference file with anchor links. Takes 10 minutes, instantly improves usability, and probably gets you +1-2 points toward Ease of Use.

## Table of Contents...

AI-Detected Topics

Extracted using NLP analysis

Claude CLI CLI OpenCode OpenCode CLI Environment Variables headless LLM local models vertex Model Format model

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