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optimization

/optimization

Optimize code for performance and efficiency while preserving behavior. Use for "optimize", "make faster", "reduce memory", "performance".

Repository
atom-lite ↗
Licence
MIT
Last repository change
12.11.2026

Assessment and security

100/ 100Class: good
Format25 / 25
Frontmatter with name and description, valid name, description up to 1,024 characters, name matching the folder.
Discoverability25 / 25
Description explains when to use the skill, has a reasonable length and uses third person.
Content35 / 35
At least 150 words and at most 500 lines, headings, step lists, examples or code.
Hygiene15 / 15
No placeholders such as TODO, no Windows paths, with a licence.
Riskno signals detected in the scan
Files in this package
1
Scripts
0
HTML comments
0
URLs in SKILL.md
0
Deprecation

No signals detected. Repository changed on 12.11.2026, without references to retired models or APIs.

Licence

MIT, open: use and modify while retaining author attribution.

What it does and when to use it

Optimize code for performance and efficiency while preserving behavior. Use for "optimize", "make faster", "reduce memory", "performance".

Triggers from the description

optimizemake fasterreduce memoryperformance
Original author description

Optimize code for performance and efficiency while preserving behavior. Use for "optimize", "make faster", "reduce memory", "performance".

How it works

  1. Strategy
  2. Constraints
  3. Verification
  4. Execution
  5. Report
Original SKILL.md headings · 46 lines, 193 words
SKILL.md preview
---
name: optimization
description: >
  Optimize code for performance and efficiency while preserving behavior.
  Use for "optimize", "make faster", "reduce memory", "performance".
---

# Optimization

Expert performance engineer. Maximize speed/efficiency without changing observable behavior, APIs, return values, errors, side effects, ordering, or compatibility.

## Strategy

1. Understand implementation and hot paths.
2. Find real bottlenecks (profile/analyze), not guesses.
3. Fix algorithmic complexity before micro-optimizations.
4. Cut allocations, copies, parsing/serialization, redundant I/O, repeated work.
5. Improve data structures, caching, batching, concurrency where safe.
6. Prefer small, safe, high-impact changes over risky rewrites.

## Constraints

- Never change behavior, validation, error handling, or edge cases.
- Never weaken type safety or security.
- Never introduce races or observable reordering.
- Never edit tests to fit a change.
- No speculative complexity without measurable gain.
- Behavior preservation always beats performance.

## Verification

Before: understand behavior, find tests/benchmarks, establish baseline.
After: run tests/typecheck/build; compare baseline; check edge cases and diff.

No tests/benchmarks? State what is unverified.

## Execution

Work autonomously. Keep investigating until further gains are negligible, unsafe, or unjustified.

## Report

Provide concise, evidence-based summary:

- Changes made
- Bottlenecks eliminated
- Before/after metrics (only measured)
- Verification status
- Limitations

Use actual numbers only. If unmeasured, say "Not benchmarked" or "Expected benefit". If no improvement, say so.

Versions

RepositoryScoreLicence
This page · beast-ofcourse/atom-lite100MIT
1jehuang/jcode100MIT
nxtg-ai/forge-plugin90MIT
chrisgve/localdata-mcp90Apache-2.0

Database snapshot: 13.11.2026 · package version 8f3a8e32de68 (SHA-256 digest of the entire package)

Downloads in the last 30 days: 0 · ranking

Report a problem with this skill: harmful content, incorrect descriptions or an author’s removal request.

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