Results for “brave-search”

Run Karpathy-style autonomous ML search on a real training repo: choose the right mode (setup, program.md, bounded loop, results interpretation, or constrained-hardware adaptation), preserve the immutable prepare.py / 300-second / val_bpb contract, and route prompt/skill eval work away to LangSmith, Promptfoo, Braintrust, or skill-autoresearch.

Perform read-only web research with governed browser proposals for manual review.

Runs a structured clarifying interview for new project requests before building, then outputs a fully specified prompt.md for a fresh agent session to execute.

Runs a structured clarifying interview for new project requests before building. Instead of writing code, it outputs a fully specified prompt.md for a fresh agent session to execute, preventing expensive mistakes.

Discovers and evaluates community skills from skills.sh and awesome-openclaw-skills when local skills don't cover a need, scoring credibility and installing top recommendations with permission.

Generates comprehensive questions about decisions before implementing. Explores requirements, constraints, success criteria, edge cases, and hidden assumptions in a SINGLE comprehensive prompt. Use when starting any significant work to surface unknowns early.

Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.

Run a bounded cross-platform landscape scan before planning or implementation. Use when the real job is researching what exists, how people work around it, which solutions repeat, or how platform/tooling patterns map before deciding what to build. Produce reusable `.survey/{slug}/` artifacts, validate the artifact contract, and route planning or execution outward only after the survey is done.