optimize
Use when an algorithm-first quest should manage candidate briefs, optimization frontier, branch promotion, or fusion-aware search instead of the paper-oriented default loop.
Best for DeepScientist users needing…Works with GitHubLow risk
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@ResearAI- language
- TypeScript
★2.3kstars
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Apr 19, 2026
✦overview.md
Key Features
- ·Lightweight optimization control layer for DeepScientist
- ·Manages candidate briefs, optimization frontier, branch promotion, and fusion-aware search
- ·Uses existing DeepScientist artifact, memory, bashexec, Git, and worktree mechanisms
Use Cases
- →Algorithm-first quests requiring strongest justified optimization results
- →Scenarios where moving the optimization frontier by one justified step is prioritized over generating many low-informat…
Best for
- ✓DeepScientist users needing optimization control
- ✓Algorithm-focused development workflows
Not ideal for
- !Paper-oriented default loops
- !Non-algorithm-first quests
name
optimize
description
Use when an algorithm-first quest should manage candidate briefs, optimization frontier, branch promotion, or fusion-aware search instead of the paper-oriented default loop.
skill_role:stage
Optimize
Use this skill for algorithm-first quests where the goal is the strongest justified optimization result rather than paper packaging. The goal is to move the frontier by one justified step at a time, not to generate a large pile of low-information candidates.
This skill is the lightweight optimization control layer for DeepScientist. It does not replace the normal quest runtime. It tells you how to use the existing DeepScientist artifact, memory, bash_exec, Git, and worktree mechanisms as an optimization system.
Interaction discipline
- Follow the shared interaction contract injected by the system prompt.
- For ordinary active work, prefer a concise progress update once work has crossed roughly 6 tool calls with a human-meaningful delta, and do not drift beyond roughly 12 tool calls or about 8 minutes without a user-visible update.
- Ordinary candidate creation, smoke checks, and route updates should stay concise.
- Use richer milestone updates only when a candidate is promoted, a strong run finishes, the frontier shifts materially, or a fusion/debug route becomes the new main path.
$install
1-click copynpx skills add ResearAI/DeepScientist --skill optimizeSafety assessment
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poorThe SKILL.md content is hard to understand and quite ambiguous.
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1/ 5
not actionableThe SKILL.md is hard to act on; an agent would not know what to do.