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optimize-code

Analyze and optimize Python code performance in critical paths

60

Quality

71%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

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tessl review fix ./.claude/skills/optimize-code/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

88%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 skill is a tightly structured, highly actionable optimization workflow with strong validation checkpoints and feedback loops. Its only gaps are minor over-explanation in a few lists and a monolithic inline structure that could split reference material into bundle files.

DimensionReasoningScore

Conciseness

The body is efficient and avoids explaining concepts Claude already knows, but a few sections ('Benefits:' lists, the recursion overhead sentence) over-explain slightly and could be trimmed, fitting the 'efficient with minor over-explanation' anchor.

4 / 5

Actionability

Fully executable, copy-paste-ready code covers the common cases (slotted classes, inner-function hoisting, recursion-to-iteration, lru_cache checks, timeit one-liners, benchmark scripts and shell commands), matching the top anchor.

5 / 5

Workflow Clarity

The five-phase sequence has explicit validation checkpoints (baseline benchmark, benchmark after each change, variance checking, final optimized-vs-devel comparison, running existing tests) and feedback loops (variance >10-15% flags external factors; benchmark caches with/without), matching the top anchor.

5 / 5

Progressive Disclosure

Content is well-organized into clearly numbered phases and subsections with no nested references, but the skill is over 50 lines all inline with no bundle files, so it stops short of the well-signaled one-level-deep reference structure of the top anchor.

4 / 5

Total

18

/

20

Passed

Description

53%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 states a clear, specific purpose but lacks an explicit 'Use when...' trigger clause, capping completeness. It is concise and mostly distinct from sibling skills, though it omits common trigger synonyms.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers (e.g., 'Use when the user asks to speed up, profile, or optimize Python code, or mentions a slow hot path or critical path').

Include natural synonyms users say ('speed up', 'slow', 'faster', 'profile', 'hot path') alongside 'optimize' and 'performance' to broaden trigger coverage.

DimensionReasoningScore

Specificity

Names the domain (Python code performance) and two concrete actions ('Analyze and optimize') in 'critical paths', matching the anchor that lists domain plus 1-2 actions without comprehensive coverage.

3 / 5

Completeness

The 'what' is clear but there is no 'Use when...' clause or equivalent trigger guidance, which per the judging guidelines caps completeness at 3.

3 / 5

Trigger Term Quality

Relevant natural terms appear ('optimize', 'Python code', 'performance', 'critical paths') but common variations users would say ('speed up', 'slow', 'faster', 'profile', 'hot path') are missing, fitting the anchor with some relevant keywords but missing synonyms.

3 / 5

Distinctiveness Conflict Risk

The niche (Python performance optimization in critical paths) is clearly distinct from general coding skills with only minor overlap risk against a generic profiling or optimization skill, fitting the 'mostly distinct' anchor.

4 / 5

Total

13

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
dlt-hub/dlt
Reviewed

Table of Contents

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