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Agents tracked: 442 Downloads (7d): 202M down 19.3% GitHub stars: 10.4M Releases (7d): 693 Agent status: 1 with issuesSince last limit reset: Claude 28d · Codex 1d Updated Oct 21, 2026
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StarSkirmish Bench v0.2: LLMs write StarCraft bots in one hour with first-party CLIs

StarSkirmish Bench v0.2 gives each of nine LLMs one hour to write a Protoss bot in C++ for StarCraft: Brood War, using the lab's own CLI harness. Bots are scored by win rate against a fixed roster of human-written and demo bots, and GPT-6 Astra scores highest.

The problem

Common coding and reasoning benchmarks may not reflect how well models handle long-horizon agentic coding. The benchmark's authors wanted a test where a model has to write a working bot, practice against opponents and use what it learns to improve the bot within a fixed time limit.

How they did it

  1. Each model starts from a skeleton bot that only mines, plus three demo bots and the FAP and BWEM libraries, for BWAPI 4.4.0 on OpenBW.
  2. The model runs for one hour in its lab's first-party CLI (Claude Code, Codex, Antigravity CLI or Muse Code) at the highest reasoning effort available, with web search and fetch disabled.
  3. Tools let the agent compile its bot, play practice games against tiered opponents, and read game summaries, transcripts and its bot's log.
  4. Whatever is in the bot folder when the hour ends becomes the final bot; there is no submit step.
  5. Each model's 5 final bots play the 13 roster bots 6 times on each of three maps, and the model's score is the average win rate of those bots.

Results

  • As reported by StarSkirmish, GPT-6 Astra scored highest, ahead of GPT-6.1 Sol in second place.
  • As reported by StarSkirmish, Gemini 4 Argon, Claude Opus 5.5 and Claude Fable 5.1 were functionally tied, all scoring between 37 and 39.
  • As reported by StarSkirmish, the best model, GPT-6 Astra, won only 7% of its games against Stardust, PurpleWave and BananaBrain.
  • As reported by StarSkirmish, the number of practice games against the 7 strongest bots was the strongest predictor of score, and Gemini 4 Argon's best and worst runs were 18 points apart.

As reported by the source (StarSkirmish benchmark report); AgentGid did not measure these figures.

Takeaway. When an agent has a limited time budget, having it test its work early against strong opponents is a better predictor of final quality than the model's standing on common benchmarks.
AgentGid's take

This suits someone comfortable in C++ and the BWAPI toolchain who wants to benchmark models or reproduce the harness, not a casual builder. Note that every result is reported by StarSkirmish, and run-to-run variance was large (Gemini 4 Argon's best and worst runs were 18 points apart), so one attempt tells you little. To try the workflow cheaply, OpenCode (Free + $10/mo) accepts any provider key.

The agents used here

Compare: Claude Code vs Antigravity CLI

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