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Ask Neo for optimization suggestions on a function, file, or hot path. Targets algorithmic improvements, redundant work, allocation/hot-loop issues — not micro-style.
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Based on SOC occupation classification
Get Neo's architectural guidance for design decisions. Trade-off analysis for choices like microservices vs monolith, sync vs async, event-driven vs request-response — with persistent memory of how similar decisions played out.
Ask Neo to help debug intermittent, complex, or hard-to-reproduce issues. Particularly useful for race conditions, memory issues, distributed-systems bugs, and cases where the symptom is not the root cause.
Ask Neo to extract a reusable pattern from a piece of code, or to find existing patterns in the codebase that match a description. Useful for codifying conventions and finding duplicated logic.
Get Neo's code review with semantic pattern matching. Focuses on security vulnerabilities, edge cases, error handling, and performance issues across the target file or module.
Ask Neo for semantic reasoning and code suggestions over the current codebase. Use for general questions, code suggestions, or architectural guidance backed by Neo's persistent memory.
Sync current branch with base branch. Codex (you) resolves conflicts intelligently, not automated scripts.
| name | neo-optimize |
| description | Ask Neo for optimization suggestions on a function, file, or hot path. Targets algorithmic improvements, redundant work, allocation/hot-loop issues — not micro-style. |
When the user invokes this skill ($neo-optimize <target>), do the following:
Locate the target. It may be a function name (process_large_dataset), a file, or a description ("the user-search query path"). Use Grep/Read to find the actual implementation.
Capture the current implementation plus its callers if you can do so cheaply. Neo can suggest better algorithms, but only if it sees how the code is used.
Invoke Neo with an optimization-framed prompt. Allow up to 5 minutes.
neo --mode advise <<'QUERY'
Suggest optimizations for the following code. Focus on: algorithmic improvements (lower asymptotic complexity), redundant computation, allocation in hot loops, IO batching opportunities. Skip micro-style changes.
<paste current implementation + relevant callers>
QUERY
Present Neo's suggestions ranked by expected impact. Each CodeSuggestion includes estimated_risk and blast_radius — surface those alongside the recommendation.
For high-risk changes, recommend benchmarking before applying. Neo's confidence reflects pattern-match strength, not measured speedup.