From thinking-frameworks-skills
Clusters published post corpus by theme via axial coding and Braun & Clarke's thematic analysis to surface candidate sections with cohesion scores.
npx claudepluginhub lyndonkl/claude --plugin thinking-frameworks-skillsThis skill uses the workspace's default tool permissions.
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Generates design tokens/docs from CSS/Tailwind/styled-components codebases, audits visual consistency across 10 dimensions, detects AI slop in UI.
Records polished WebM UI demo videos of web apps using Playwright with cursor overlay, natural pacing, and three-phase scripting. Activates for demo, walkthrough, screen recording, or tutorial requests.
Delivers idiomatic Kotlin patterns for null safety, immutability, sealed classes, coroutines, Flows, extensions, DSL builders, and Gradle DSL. Use when writing, reviewing, refactoring, or designing Kotlin code.
Per Curator run:
- [ ] Step 1: Read every post in corpus/published/** end-to-end (not just titles)
- [ ] Step 2: Extract 3-5 codes per post (concepts, methods, domains)
- [ ] Step 3: Group codes across posts by semantic similarity (axial)
- [ ] Step 4: Validate clusters — split or merge where needed
- [ ] Step 5: Report candidate clusters with membership, cohesion, outliers
cluster_1:
candidate_handle: "kalshi-log"
posts: [list of slugs]
cohesion: high | medium | low
centroid_codes: [top 5 codes]
outlier_posts: [weakly-attached members]
rejected_clusters: [clusters with <3 posts]
high: ≥5 posts, shared centroid, clear register.medium: 3-4 posts or mixed register.low: cluster exists but coherence is weak.recommend-prune and "watch" candidates.