optimize 100/100 — SaferSkills

Is optimize safe to install?

SaferSkills independently audited optimize (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.

CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

100

35.0 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 0 flagged

Securityscore 100 · 0 findings

✓—All security checks passedNo findings in this category for the latest scan.pass

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

skills/optimize/SKILL.md · 1 file

skills/optimize/SKILL.md2.1 KB · Markdown

description: Benchmark, analyze, and optimize a function's execution time. Produces a before/after performance table with real numbers. Never presents a change without proving it is faster.

Execute all four phases in order. Do not skip any phase.

Phase 1 — Establish Baseline

Identify the exact code to optimize.
Run a micro-benchmark:

Write a temporary micro-benchmark script in the user's workspace.
The script MUST contain a warm-up phase (discard ≥10 iterations).
The script MUST run ≥100 iterations and output the Average and P95 execution time.
Run the script using the terminal.
Delete the temporary script after recording the results.
Note: If the script fails due to missing imports or dependencies, skip it and use the bash `time` command as a fallback.

Record P95 and Average. Do not proceed until the benchmark runs without error.
Report baseline numbers before writing any new code.

Phase 2 — Algorithmic Analysis

State the current Time Complexity (Big-O) explicitly.
State the current Space Complexity and identify the primary allocation sites.
Name the bottleneck precisely:

"Nested loops causing O(n²) scaling"
"Repeated string concatenation causing N heap allocations per call"
"Full table scan caused by missing index on user_id"

Phase 3 — Refactoring

Rewrite using a more efficient algorithm or data structure (apply in priority order):

Replace Array/List lookups with Hash Sets/Dictionaries: O(N) → O(1)
Vectorization or batching instead of per-item iteration
Caching/memoization of expensive pure computations
Zero-allocation patterns and buffer reuse to reduce GC pressure
Bitwise operations where mathematically equivalent

Run the benchmark on the new code.
If the new code is not measurably faster: discard it, select a different approach, repeat.

Phase 4 — Report

Present a Performance Report table:

Metric	Baseline	Optimized	Δ
Average	Xms	Yms	-Z%
P95	Xms	Yms	-Z%

Follow with a one-paragraph explanation grounded in CPU/memory theory.

optimize— agent skill

Is optimize safe to install?

Phase 1 — Establish Baseline

Phase 2 — Algorithmic Analysis

Phase 3 — Refactoring

Phase 4 — Report

Audit the pieces. Scan the whole. Decide.