SkillCheatSheet
super-research
An AI agent skill from XiaomiMiMo/MiMo-Code, scored 73 out of 100 by code.
Code score by group
It loses the most points in Done criteria (11), the group that checks whether there is a checklist and a step that verifies the work.
What the author says it does
Autonomous research skill for open-ended, high-volume research work — an agent left running for a while (minutes to overnight) that produces honest, comparable, auditable evidence instead of a single one-shot answer. Covers eight modes selected by the request: (1) experiment loop — iteratively edit code, run, measure a metric, keep or revert (baseline → hypothesize → run → keep/revert loop; use for "optimize X", "tune hyperparameters", "run experiments overnight", "autonomously improve this model", "hill-climb a metric", "自动实验"); (2) topic survey / 主题调研 — collect and synthesize sources on a q…
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- XiaomiMiMo/MiMo-Code
- Folder
- packages/cli/src/skill/builtin/.bundle/super-research
- License
- MIT
- GitHub stars
- 13,781
- SKILL.md lines
- 91
- Other files
- 33
Add super-research to your agent
npx skills add XiaomiMiMo/MiMo-Code --skill super-researchThe command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.
Labelled for
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All skills in XiaomiMiMo/MiMo-Code
Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.