# Bora Celik (@xBora) on x

- id: koinon:creator:x_xbora
- url: https://koinonlink.com/kol/x/xBora
- schema_version: 1.4

## Identity
- platform: x
- handle: xBora
- platform_url: https://twitter.com/xBora
- website: https://gentic.co
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 1863
- following: 508
- posts_total: 28
- posts_observed: 15
- posts_per_day: 0.004
- account_age_days: 6786
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00054
- best_post_interactions: 1
- 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: 0.95
- category_source: derived_from_recent_content
- topics: AI agent development, MCP (Multi-Agent Coordination Platform), AI project time allocation, Agent architecture design, AI automation engineering, Technical planning for AI agents
- bio: Founder @ https://t.co/ZErBKv69xM

## Audience (inferred)
- status: present
- description: AI agent builders and technical founders focusing on AI automation, especially those working on multi-agent systems and agent architecture
- roles: automation
- seniority: practitioner
- pain_points: Struggling with the time spent on actual agent logic versus infrastructure and coordination layers, Finding it hard to estimate how much effort goes into building the core agent vs. the supporting framework, Lacking clear benchmarks or frameworks for structuring AI agent projects, Difficulty in prioritizing development efforts between agent logic and MCP (Multi-Agent Coordination Platform) setup
- posts_analysed: 1
- confidence: 0.4

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

## Quality signals
- authenticity_score: 55
- authenticity_basis: engagement_observed
- credibility_score: 55
- flagged_for_review: false
- koinon_bd_grade: B — 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_xbora#9399d7f3] 5% - 30% - 65% What % of our time goes into building the actual agent in an AI agent project? In my experience the answer is 5%. 30% goes into building the MCP servers and MCP tools that act as a connector between the agent and the data. And a whopping 65% goes into making sure t (https://twitter.com/xBora/status/2064733073531416960)

## 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=21, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=21, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=21, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=80, 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=80, 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=0.5, freshness_days=80, 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: 80
- audience_updated_days_ago: 21

## 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_xbora
- Request removal: https://koinonlink.com/claim?k=x_xbora
- Terms: https://koinonlink.com/for-ai