dart-logic-patterns
Best practices for implementing efficient business logic on mobile using appropriate algorithms and data structures.
33
17%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/dart/dart-logic-patterns/SKILL.mdQuality
Discovery
0%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is too abstract and vague to be useful for skill selection. It reads like a course title rather than an actionable skill description, lacking concrete actions, natural trigger terms, and any explicit guidance on when to use it. It would be nearly impossible for Claude to reliably select this skill over others in a multi-skill environment.
Suggestions
Replace abstract language with specific concrete actions, e.g., 'Implements sorting algorithms, caching strategies, and efficient data lookups for mobile apps' instead of 'appropriate algorithms and data structures'.
Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks about optimizing mobile app performance, choosing data structures for iOS/Android, or implementing efficient search, sort, or caching logic on mobile.'
Narrow the scope to a distinct niche to reduce conflict risk, e.g., focus on a specific platform (iOS/Android), specific patterns (offline-first, pagination), or specific problem types (real-time data sync, local caching).
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description uses vague, abstract language like 'best practices', 'efficient business logic', and 'appropriate algorithms and data structures' without listing any concrete actions. It describes a general topic area rather than specific capabilities. | 1 / 3 |
Completeness | The description weakly addresses 'what' (best practices for business logic) but provides no 'when' clause or explicit trigger guidance. There is no 'Use when...' or equivalent, and the 'what' itself is too vague to be useful. | 1 / 3 |
Trigger Term Quality | The terms used are overly generic and academic ('business logic', 'algorithms and data structures', 'mobile'). Users are unlikely to phrase requests using these exact abstract terms; they would more likely ask about specific tasks like 'sort a list on iOS' or 'optimize database queries in Android'. | 1 / 3 |
Distinctiveness Conflict Risk | The description is extremely generic and could overlap with virtually any mobile development skill, algorithm skill, or general coding best practices skill. 'Business logic', 'algorithms', and 'data structures' are broad enough to conflict with many other skills. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
35%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads as a high-level reference card of algorithmic best practices for mobile development, but it lacks the concrete, executable guidance that would make it truly actionable. It explains concepts Claude already knows (data structures, Big O, debouncing) without providing Flutter/Dart-specific code examples or decision frameworks. The content would benefit significantly from concrete code snippets and clearer thresholds for when to apply each technique.
Suggestions
Add concrete Dart/Flutter code examples for each pattern (e.g., a debounce implementation, a binary search usage, a memoization example with package:memoize).
Remove or drastically shorten explanations of concepts Claude already knows (Big O, what Map/Set/List are) and focus on mobile-specific thresholds and gotchas.
Add a decision framework or quick-reference table (e.g., 'dataset size > 500 items on main thread → offload to isolate; < 100 → inline sort is fine').
Include links to example files or deeper references for complex topics like validation layer organization or custom Comparable implementations.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient but includes some explanations Claude already knows (e.g., what Map, Set, List are for, what Big O is, what debouncing/throttling mean). These are standard CS concepts that don't need defining. | 2 / 3 |
Actionability | The content is entirely descriptive with no executable code, no concrete examples, and no specific commands. It reads like a textbook summary rather than actionable guidance—e.g., 'Use debouncing' without showing how to implement it in Dart/Flutter. | 1 / 3 |
Workflow Clarity | The content is organized into logical categories, but there's no sequenced workflow, no decision tree for choosing approaches, and no validation steps. For a conceptual skill this is acceptable but could benefit from a decision framework (e.g., 'if dataset > X, use Y'). | 2 / 3 |
Progressive Disclosure | The content is reasonably structured with clear section headers, but everything is inline with no references to deeper resources. Some sections (like memoization or validation logic) could benefit from linking to example files or more detailed guides. | 2 / 3 |
Total | 7 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Repository
- dhruvanbhalara/skills
- Commit
cf4f343
- Reviewed
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