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The workflow is language-agnostic. Language detection is automatic — toolchain and conventions come from instruction files (go.md, python.md, typescript.md).
Replace the placeholder strings in opencode.json with your provider and model ID (e.g., anthropic/claude-opus-4-5, openai/gpt-4o). See instructions/model-tiers.md for the full configuration guide.
Serena Integration
Serena provides semantic code navigation and persistent project memory via MCP.
Memory taxonomy:
Category
Purpose
build-and-test/
Build commands, test runner setup, CI configs
repo-structure/
Directory layout, key packages, entry points
architecture-invariants/
Patterns that must not be broken
observability-conventions/
Logging, metrics, tracing standards
recurring-pitfalls/
Known failure modes and gotchas
local-dev-notes/
Environment-specific setup notes
Memory is context-aware — commands load relevant categories automatically. Use /memory-cleanup to check for staleness, duplicates, and propose new memories on a regular cadence.
Customization
Use the config authoring commands to extend this setup:
/agent-draft + /agent-create — add a new specialized subagent
/command-draft + /command-create — add a new workflow entry point
/skill-draft + /skill-create — add a new composable skill
Run /validate-config after any structural change to check references and formatting.
Requirements
OpenCode installed
Serena CLI on PATH
TypeScript runtime (Bun or Node with tsx) for custom tools
Optional: Go toolchain (for Go workflows)
Optional: Python with pytest and ruff (for Python workflows)