topic-brainstormer

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Generate blog topic ideas: problem mining, gap analysis, expansion.

AI & Automation 425 stars 46 forks Updated yesterday MIT

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Quality Score: 96/100

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Skill Content

# Topic Brainstormer Generate blog topic ideas that align with a content identity built around solving frustrating technical problems. Three phases: ASSESS, DECIDE, GENERATE. Every topic must pass the three-question content quality filter before presentation. ## Deep References | Signal | Load | Content | |---|---|---| | Filtering topics: three-question test, category examples | `references/content-filter.md` | Full quality filter with green/red/yellow topic categories, salvage patterns | | Scoring: impact, vex, resolution matrix | `references/priority-scoring.md` | Rubrics per dimension, score ranges, calibration, worked examples | | Mining: problem sources, gap analysis, expansion | `references/topic-sources.md` | Mining prompts, signal strength, gap types, expansion strategies | ## Phase 1: ASSESS Gather context about existing content and available sources. 1. Read all posts in the content directory. Document post count, content clusters, technologies covered, last post date. 2. Identify available sources: problem mining (recent debugging, errors, config struggles), gap analysis (cross-references leading nowhere), tech expansion (adjacent technologies). 3. Extract all "see also" and cross-reference mentions. Flag any pointing to content that does not exist. **Gate**: Content landscape documented, at least 2 sources identified with material. ## Phase 2: DECIDE Generate candidates and filter through the content quality test. 1. Mine 5-10 raw candidates from at leas...

Details

Author
notque
Repository
notque/vexjoy-agent
Created
6 months ago
Last Updated
yesterday
Language
Python
License
MIT

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