edit-model-code
edit-model-code is an Agent behaviour & coding discipline skill for AI agents, published by vlasenkoalexey in the tpu_performance_autoresearch_wiki repository on GitHub. Skillspace rates edit-model-code D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Coding-discipline guidelines for surgically modifying model code inside a per-experiment fork in the autoresearch loop. Adapts Andrej Karpathy's LLM-coding guidelines (think before coding, simplicity first, surgical changes, goal-driven execution) to this project's invariants — no semantics drift, one mechanism per experiment, the training run is the test, no kernel fallbacks. Invoke BEFORE opening any model-code file in the experiment fork (step 4 of program.md's "experiment loop"). Helps weaker LLMs stay disciplined under autoresearch-loop pressure where the agent is autonomous and can't ask clarifying questions. NOT for wiki edits, infra scripts, or trunk merges — those are out of scope.
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 45
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 83 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.