# MinionLab (@MinionLabAI) on x

- id: koinon:creator:x_minionlabai
- url: https://koinonlink.com/kol/x/MinionLabAI
- schema_version: 1.4

## Identity
- platform: x
- handle: MinionLabAI
- platform_url: https://twitter.com/MinionLabAI
- website: https://linktr.ee/minionlab
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 14720
- following: 37
- posts_total: 1046
- posts_observed: 2
- posts_per_day: 0.747
- account_age_days: 1400
- verified: true
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00217
- best_post_interactions: 32
- measurement_source: x_post_interactions
- measurement_formula: interactions on one post — likes, or likes + reposts + replies depending on the discovery path (the two are not distinguishable in the stored data)
- comparable_pool: peak_interactions
- status_note: We have only the single best observed post, so no mean exists. peak_post_engagement_rate is an UPPER BOUND, systematically higher than an average — never compare it against an average rate.
- 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: 0.9
- category_source: derived_from_recent_content
- topics: Open-weight AI models, AI reasoning reliability, Data traceability in AI tools, Marketing metrics vs purchase confidence
- bio: Contribute to the Future of AI with MinionLab!

## Audience (inferred)
- status: present
- description: AI practitioners and enthusiasts interested in open models, AI reasoning limits, and data traceability in tools
- roles: general_ai
- seniority: practitioner
- pain_points: AI dashboards lacking traceable sources for insights, Closed AI systems limiting transparency and control, Brands relying on vanity metrics instead of purchase signals, Fragile AI reasoning exposed by simple challenges
- posts_analysed: 4
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.85
- promotion_intent: 0.9
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 84
- authenticity_basis: engagement_observed
- credibility_score: 84
- flagged_for_review: false
- koinon_bd_grade: A — 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_minionlabai#506b4653] Most brands still measure attention. Mentions. Reach. Engagement. Share of voice. But attention is not purchase confidence. The real question is: after people notice you, what still stops them from buying? That answer usually lives in the comments. https://t.co/4Y0G0f995D (https://twitter.com/MinionLabAI/status/2069828316300026234)
- [x_minionlabai#1c8074d3] Most AI dashboards give you conclusions. DataScaler gives you receipts. Every trend, sentiment shift, competitor signal, and risk alert should trace back to the real post, comment, or review that caused it. In 2026, brand intelligence without evidence is just a prettier hallucina
- [x_minionlabai#6080001f] The fastest way to break an AI’s reasoning framework: “Are you sure?” Even when it was right, you can almost hear the model panic-searching its own soul. Humans invented a one-line adversarial prompt by accident. https://t.co/ywedbp3C6z
- [x_minionlabai#5d29af3a] Open-weight AI is starting to look like the Linux moment for intelligence. Not because open model

## 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=76, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=77, 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=77, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=119, 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=0.5, freshness_days=77, 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=119, 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=119, method=platform_profile

## Freshness
- profile_checked_days_ago: 119
- content_analysed_days_ago: 77
- audience_updated_days_ago: 76

## AI retrieval
- indexing_requests: 8
- 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_minionlabai
- Request removal: https://koinonlink.com/claim?k=x_minionlabai
- Terms: https://koinonlink.com/for-ai