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ce-optimize
Cursor Skill
Run metric-driven iterative optimization loops. Define a measurable goal, build measurement scaffolding, then run parallel experiments that try many approaches, measure each against hard gates and/or LLM-as-judge quality scores, keep improvements, and converge toward the best solution. Use when optimizing clustering quality, search relevance, build performance, prompt quality, or any measurable outcome that benefits from systematic experimentation. Inspired by Karpathy's autoresearch, generalized for multi-file code changes and non-ML domains.
AI-powered development tools for code review, research, design, and workflow automation.
Skills39
ce-agent-native-architectureBuild applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
ce-agent-native-auditRun comprehensive agent-native architecture review with scored principles
ce-brainstormExplore requirements and approaches through collaborative dialogue before writing a right-sized requirements document and planning implementation. Use for feature ideas, problem framing, when the user says 'let's brainstorm', or when they want to think through options before deciding what to build. Also use when a user describes a vague or ambitious feature request, asks 'what should we build', 'help me think through X', presents a problem with multiple valid solutions, or seems unsure about scope or direction — even if they don't explicitly ask to brainstorm.
ce-clean-gone-branchesClean up local branches whose remote tracking branch is gone. Use when the user says "clean up branches", "delete gone branches", "prune local branches", "clean gone", or wants to remove stale local branches that no longer exist on the remote. Also handles removing associated worktrees for branches that have them.
ce-code-reviewStructured code review using tiered persona agents, confidence-gated findings, and a merge/dedup pipeline. Use when reviewing code changes before creating a PR.
Subagents49
ce-adversarial-document-reviewerConditional document-review persona, selected when the document has >5 requirements or implementation units, makes significant architectural decisions, covers high-stakes domains, or proposes new abstractions. Challenges premises, surfaces unstated assumptions, and stress-tests decisions rather than evaluating document quality.
ce-adversarial-reviewerConditional code-review persona, selected when the diff is large (>=50 changed lines) or touches high-risk domains like auth, payments, data mutations, or external APIs. Actively constructs failure scenarios to break the implementation rather than checking against known patterns.
ce-agent-native-reviewerReviews code to ensure agent-native parity -- any action a user can take, an agent can also take. Use after adding UI features, agent tools, or system prompts.
ce-ankane-readme-writerCreates or updates README files following Ankane-style template for Ruby gems. Use when writing gem documentation with imperative voice, concise prose, and standard section ordering.
ce-api-contract-reviewerConditional code-review persona, selected when the diff touches API routes, request/response types, serialization, versioning, or exported type signatures. Reviews code for breaking contract changes.