data-fetching-architecture
data-fetching-architecture is a Frontend state & data fetching skill for AI agents, published by lobehub in the lobehub repository on GitHub. Skillspace rates data-fetching-architecture C (71/100) and it passed the safety scan; a judge model has also reviewed it.
Use for client APIs, SWR hooks, cache invalidation, async errors, useEffect migration, home first paint and persistent caches.
- Grade
- C
- Quality
- 71 / 100
- Safety
- Passed
- GitHub stars
- 82,440
Placed #5 of 6 in the judged category final for Frontend state & data fetching.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #5 of 6 in the judged category final for Frontend state & data fetching.
- Trigger
75 75 - Instructions
82 82 - Specificity
88 88 - Safety
85 85 - Disclosure
85 85 - Maintenance
78 78
Good layered architecture with do/don't rules and links to live source, though the description reads as a bare keyword list.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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