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Writing & Content · By akseolabs-seo
Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | 1.Voice Deep analysis of user's historical posts and comment replies to build a comprehensive Brand Voice profile. | akseolabs-seo/ | 275 | — | ~2k | Automated safety check: Notes | MIT | 3 mo ago |
| 2 | 2.Optimize Self-contained compound loop: read threadsskilllearnings.log, cluster the misses, propose concrete sub-skill rule edits, and apply them with the user's approval. | akseolabs-seo/ | 275 | — | ~1.8k | Automated safety check: Pass | MIT | 3 mo ago |
| 3 | 3.Panel Launch or prepare the optional local visual panel for AK-Threads-Booster. | akseolabs-seo/ | 275 | — | ~873 | Automated safety check: Notes | MIT | 3 mo ago |
| 4 | 4.Topics Mine insights from comments and historical data to recommend the next worthwhile topics. | akseolabs-seo/ | 275 | — | ~1.8k | Automated safety check: Notes | MIT | 3 mo ago |
| 5 | 5.Update Check AK-Threads-Booster for upstream GitHub updates, safely fast-forward the local skill repo, or install an opt-in weekly Codex automation that keeps the skill on the latest version. | akseolabs-seo/ | 275 | — | ~1.1k | Automated safety check: Notes | MIT | 3 mo ago |
| 6 | 6.Draft Select a topic and generate a draft based on the user's Brand Voice. | akseolabs-seo/ | 275 | — | ~2.6k | Automated safety check: Pass | MIT | 3 mo ago |
| 7 | Threads growth operating system for topic selection, drafting, analysis, prediction, review, and tracker refresh based on the user's own post history. | akseolabs-seo/ | 275 | — | ~2.3k | Automated safety check: Pass | MIT | 3 mo ago |
| 8 | 8.Predict Estimate likely 24-hour post performance from the user's historical data. | akseolabs-seo/ | 275 | — | ~2.2k | Automated safety check: Notes | MIT | 3 mo ago |
| 9 | 9.Analyze Decision-first analysis for a finished Threads post: style matching, psychology analysis, algorithm alignment, upside drivers, suppression risks, and AI-tone detection. | akseolabs-seo/ | 275 | — | ~1.8k | Automated safety check: Pass | MIT | 3 mo ago |
| 10 | 10.Review Post-publish feedback loop: collect actual metrics, compare against predictions, update the tracker, refresh style conclusions carefully, and learn from deviations. | akseolabs-seo/ | 275 | — | ~1.9k | Automated safety check: Pass | MIT | 3 mo ago |
| 11 | 11.Setup Initialize AK-Threads-Booster: import historical posts, normalize them into the tracker schema, auto-generate a personalized style guide, and build a concept library. | akseolabs-seo/ | 275 | — | ~1.7k | Automated safety check: Notes | MIT | 3 mo ago |
