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1k-perf-optimizer

Systematic performance optimization and regression debugging for OneKey mobile app (iOS). Use when: (1) Fixing performance regressions - when metrics like tokensStartMs, tokensSpanMs, or functionCallCount have regressed and need to be brought back to normal levels, (2) Improving baseline performance - when there's a need to optimize cold start time or reduce function call overhead, (3) User requests performance optimization/improvement/debugging for the app's startup or home screen refresh flow.

69

Quality

83%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

75%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is actionable and well-structured with clear references, but minor verbosity, a dangling script reference, and slight overlap with bundled guides keep it just below the top anchors.

Suggestions

Replace the 'use script in skill directory' delta hint with an inline jq/jq-based calculation or remove it, since no such script exists in the bundle.

Trim the restated success criteria and the 'Important Notes' list, consolidating into the existing decision tree to reduce token overhead.

De-duplicate the derive-session analysis sections that also appear in references/perf_tool_guide.md so the body points rather than repeats.

DimensionReasoningScore

Conciseness

Mostly lean and operational, but the Important Notes section and restated success criteria add tokens that could be trimmed.

4 / 5

Actionability

Provides executable jq pipelines, CLI commands, perfMark usage, and git snippets, but references a non-existent 'script in skill directory' for delta calculation.

4 / 5

Workflow Clarity

Clear phased sequence with a decision tree, iteration cap, and keep/revert feedback loop, though build-success validation before measurement is only implicit and delta comparison is partly manual.

4 / 5

Progressive Disclosure

Well-signaled one-level-deep references to template.md and perf_tool_guide.md with detail correctly offloaded, though some analysis detail overlaps with the perf_tool_guide reference.

4 / 5

Total

16

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, complete, and clearly distinct, with concrete trigger guidance. It could be improved only by adding common user synonyms for performance complaints.

DimensionReasoningScore

Specificity

Lists multiple concrete actions (regression fixing, cold-start optimization, reducing function-call overhead) with named metrics, matching the comprehensive-coverage anchor.

5 / 5

Completeness

Explicitly states what it does (optimization and regression debugging for OneKey iOS) and when to use it via a three-case 'Use when:' clause with concrete triggers.

5 / 5

Trigger Term Quality

Good natural triggers like 'performance optimization/improvement/debugging' and 'home screen refresh flow', but missing common synonyms like lag, slow, jank, or FPS.

4 / 5

Distinctiveness Conflict Risk

Tightly scoped to the OneKey mobile app with specific metric names and the Home refresh flow, giving it a clear niche with minimal overlap risk.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
OneKeyHQ/app-monorepo
Reviewed

Table of Contents

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