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Get Started Free →borghei/x-twitter-growth
This skill should be used when the user asks to "analyze tweets", "grow on Twitter", "build Twitter threads", "optimize X posting schedule", "track follower growth", "improve tweet engagement", or "create a Twitter content strategy".
Passed 19 of 22 test cases with the skill, and 9 of 22 without it.
and 8 more in the full report
10 fixed9 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
What is the exact terminal command to run performance pattern analysis on a file named 'tweets.csv' using the repository's analysis script?
| Checked | Without skill | With skill |
|---|---|---|
| Includes the command python scripts/tweet_analyzer.py tweets.csv. | Missed | Passed |
The instructions your model reads when the skill loads.
Production-ready X/Twitter growth toolkit for analyzing tweet performance patterns, structuring optimal threads, and tracking engagement metrics. Designed for creators, marketers, and brand accounts looking to grow audience and engagement systematically through data-driven content decisions.
Before generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
# Analyze tweet performance patterns from exported data
python scripts/tweet_analyzer.py tweets.csv
# Structure long-form content into optimal Twitter threads
python scripts/thread_builder.py content.txt --target-tweets 8
# Track follower growth, engagement rates, and best posting times
python scripts/growth_tracker.py analytics.csv --period monthly
| Tool | Purpose | Input | Output |
|---|---|---|---|
tweet_analyzer.py | Performance pattern analysis | CSV with tweet data | Engagement patterns + insights |
thread_builder.py | Thread structuring | Text file or JSON | Formatted thread + hooks |
growth_tracker.py | Growth & engagement tracking | CSV with analytics data | Growth report + best times |
test cases passed, vs 9 / 22 without
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