LLM Token Optimization for OpenCode

• • opencode
  • ai|LLM

  My token budget is starting to burn fast. Here are the token optimizations I've done to reduce the cost for OpenCode.

  • Install RTK.
    • Reduce shell output. See here for the supported commands.
  • Install Codegraph.
    • Remember to codegraph init new repository !
    • Make sure that the MCP server is live.
  • Install OpenSlimedit.
    • The code source is very tiny. It basically compress built-in tool descriptions that are frequently used, and perform additional little optimisations here and there.
  • Use cheaper models for subagents.

  Excluded plugins

  • Dynamic Context Pruning Plugin : Not particularily convinced that it would reduce cost. Especially when I read their section Impact on Prompt Caching that kinda confirm my skepticism :

    Trade-off: Pruning reduces context size but can increase cache misses. The cost balance depends on your conversation, compression frequency, and provider pricing.

    Cache misses were exactly a significant part of my tokens cost. No point to risk it only to figure out what "intelligently" managed conversation ever mean.

  • OpenCode Snip : Used to reduce the output of shell commands. Most certainly redunding with RTK.

  Publié il y a 2 sem. · Mis à jour la semaine dernière

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