# UnderBuilt (@underbuilt_) on x

- id: koinon:creator:x_underbuilt_
- url: https://koinonlink.com/kol/x/underbuilt_
- schema_version: 1.4

## Identity
- platform: x
- handle: underbuilt_
- platform_url: https://twitter.com/underbuilt_
- website: https://www.wvhdevelopments.com/
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 515
- following: 1006
- posts_total: 4010
- posts_observed: 6
- posts_per_day: 4.69
- account_age_days: 855
- verified: true
- size_tier: nano

## Engagement
- status: not_collected
- status_note: Engagement has not been collected for this creator yet. This is a gap in our collection, NOT a statement that the creator has no engagement. Follower count is known, so it is measurable.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: software
- subcategory: ai_tools
- category_confidence: 0.8
- category_source: derived_from_recent_content
- topics: 游戏化工程教育工具, 学习方法的迭代优化, AI辅助自学系统, 工程学生日常学习与开发结合
- bio: Mech Eng • Custom Software & Automations • Robotics SaaS loading...

## Audience (inferred)
- status: present
- description: mechanical engineering students and early-career engineers interested in self-learning tools, gamified education, and AI-powered learning
- roles: none
- seniority: learner
- pain_points: inefficient learning with traditional university courses and slow feedback loops, lack of personalized, iterative improvement mechanisms, high costs of AI tools making sustained use difficult, difficulty in mastering engineering knowledge through gamified approaches
- posts_analysed: 7
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.8
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 35
- authenticity_basis: profile_shape_only
- credibility_score: 35
- flagged_for_review: false
- koinon_bd_grade: C — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [x_underbuilt_#ee6a0cac] Building a tool to help me learn better than uni... https://t.co/rqM5Bj6Wzd (https://twitter.com/underbuilt_/status/2073400567406199136)
- [x_underbuilt_#6f550e53] More lessons being improved as i study more... Learn something Feedback on how i learnt that thing improve the way i learnt that thing for the next thing https://t.co/KRXkbocwPT
- [x_underbuilt_#810032e5] Just spent another study session inside Assembly Labs. The best part? The more I learn, the more I spot things to improve. Using the product every day means it gets better every day. Better ui, better features, better simulations, better learning. Build. Use. Improve. Repeat. htt
- [x_underbuilt_#220b3397] claude gifted me $100 fable credit and that mf went in one prompt i see how companies are spending millions a month !
- [x_underbuilt_#f4bbe22f] dev gym eat study dev gym eat study https://t.co/q0aGyv5PcP
- [x_underbuilt_#5070a846] Starting the maths module on https://t.co/VhZPBWFfAG https://t.co/2iOygt6FqT
- [x_underbuilt_#2187a46f] Engineers: If there was software that taught engineering through a gamified,

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=78, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=78, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=78, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=78, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=78, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=108, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.25, freshness_days=78, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=108, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=108, method=platform_profile

## Freshness
- profile_checked_days_ago: 108
- content_analysed_days_ago: 78
- audience_updated_days_ago: 78

## AI retrieval
- indexing_requests: 7
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=x_underbuilt_
- Request removal: https://koinonlink.com/claim?k=x_underbuilt_
- Terms: https://koinonlink.com/for-ai