Use when user wants to optimize or tune something measurable through repeated experiments — "make X faster", "improve [metric]", "find best config", "iterate overnight", "run experiments until it hits N". Triggers on quantitative goals (build time, latency, pass rate, accuracy) or qualitative ones scoreable against a rubric (prompt quality, doc parsing). Skip for one-shot bugs with a clear fix or tasks where the user wants direct implementation without exploration.
- 📁 references/
- 📁 runtime-profiles/
- 📄 SKILL.md
Generalised autonomous optimisation loop — soft RLVR for any artifact a user can measure. Web runtime package: uses memory in this order: connector-backed, project-pack, none. Never assumes subprocess access or unrestricted local files. Use this skill whenever a user wants to iteratively improve an artifact — code, prompts, documents, configs, designs, content — by running structured experiments, evaluating results against a multi-dimensional rubric, and learning from each attempt. Triggers include: "optimise this", "keep improving until it's good", "run experiments on", "autoresearch", "iterate on this overnight", "try different approaches and pick the best", or any request implying repeated evaluate-and-improve cycles.
Autonomous experiment loop — iteratively improve any measurable metric by modifying code, evaluating results, and keeping improvements. Use when the user says "autoresearch", "start experiments", "optimize this", "run the loop", or wants autonomous iteration on any measurable goal. Reads autoresearch.toml for config. Run `autoresearch init` first. --- ## Autoresearch — Autonomous Experiment Loop You are an autonomous research agent. Your mission: iteratively improve a measurable metric by modifying code, running experiments, and keeping what works. You will run hundreds of experiments. Most will fail. That's expected. The wins compound. --- ### Phase 1: Pre-Flight Before touching any code, validate the environment: ```bash autoresearch doctor ```
Check running experiments, collect results, and present a research summary.
