Flask patterns -- application factory, blueprints, error handlers, extensions, request lifecycle, configuration, logging, CLI commands
98
98%
Does it follow best practices?
Impact
98%
1.28xAverage score across 5 eval scenarios
Passed
No known issues
Quality
Discovery
100%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 is a well-crafted skill description that excels across all dimensions. It provides comprehensive coverage of Flask-specific capabilities with concrete patterns listed, includes natural trigger terms users would actually use, and has an explicit 'Use when' clause with multiple relevant scenarios. The Flask-specific terminology makes it highly distinctive and unlikely to conflict with other skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and concepts: 'application factory, blueprints, error handlers, extensions, request lifecycle, configuration, logging, CLI commands, and project structure' - these are all specific Flask patterns and components. | 3 / 3 |
Completeness | Clearly answers both what (Flask patterns including application factory, blueprints, etc.) AND when with explicit 'Use when' clause covering multiple scenarios: building/reviewing Flask APIs, setting up new projects, migrating apps, or choosing patterns. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'Flask', 'APIs', 'Flask project', 'blueprints', 'single-file app', 'structured project', 'Flask patterns'. These cover common variations of how users would describe Flask-related work. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with Flask-specific terminology throughout. The combination of 'Flask', 'blueprints', 'application factory' creates a clear niche that wouldn't conflict with general Python or other web framework skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is an excellent skill document that demonstrates Flask best practices through concrete, executable examples with clear WRONG/RIGHT contrasts. The content is comprehensive yet concise, covering the full application lifecycle from project structure through testing. The checklist and verifier references provide clear validation checkpoints.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, using WRONG/RIGHT patterns to show contrast without over-explaining. It assumes Claude knows Python and Flask basics, focusing only on patterns and anti-patterns that matter. | 3 / 3 |
Actionability | Every section provides complete, executable code examples that can be directly copied. The project structure, factory function, blueprints, error handlers, and test fixtures are all production-ready implementations. | 3 / 3 |
Workflow Clarity | The skill clearly sequences how components connect: extensions.py → create_app() → blueprints → error handlers. The checklist at the end provides explicit validation steps, and the testing section shows the verification workflow. | 3 / 3 |
Progressive Disclosure | Content is well-organized with numbered sections, clear headers, and a summary checklist. The verifiers section at the end provides one-level-deep references to related validation tools without nesting. | 3 / 3 |
Total | 12 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (512 lines); consider splitting into references/ and linking | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
Reviewed
Table of Contents