# Box (@Box) on x

- id: koinon:creator:x_box
- url: https://koinonlink.com/kol/x/Box
- schema_version: 1.4

## Identity
- platform: x
- handle: Box
- platform_url: https://twitter.com/Box
- website: https://developer.box.com
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 78609
- following: 3150
- posts_total: 13294
- posts_observed: 4
- posts_per_day: 1.978
- account_age_days: 6721
- verified: false
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00009
- best_post_interactions: 7
- 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: AI agent cost management, Contract review agents, Building intelligent content apps with Box
- bio: Helping devs build the future of intelligent, content-driven apps using @Box. Check out our docs and sign-up for a free developer account on https://t.co/oDLXCndOkk

## Audience (inferred)
- status: present
- description: Developers building AI agents and intelligent, content-driven apps, especially those integrating Box AI
- roles: dev
- seniority: practitioner
- pain_points: High and compounding costs of frontier models in recursive agents, Inconsistent AI outputs on complex tasks like identifying risky contract clauses
- posts_analysed: 3
- confidence: 0.4

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

## Quality signals
- authenticity_score: 48
- authenticity_basis: engagement_observed
- credibility_score: 83
- 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_box#4b4c7f3f] Frontier models are 2-3x more expensive per generation. In a recursive agent, that cost compounds across every planning, retrieval, and synthesis step. Box AI Research's answer: adaptive model selection. Frontier intelligence where it changes the outcome. Smaller models everywher (https://twitter.com/Box/status/2072758984885539183)
- [x_box#69b90ac5] https://t.co/34mD3Wuna3
- [x_box#452f70b2] Your contract review agent can read an NDA and summarize the key terms. But ask it "what are the risky clauses?" and you get a different answer every time. Neither gets solved by a bigger model. Here's a deep dive of the Box AI Extract NDA risk workflow. The agent calls POST /2.0

## 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=77, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=77, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=77, 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=109, 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=109, 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=109, method=platform_profile

## Freshness
- profile_checked_days_ago: 109
- content_analysed_days_ago: 77
- audience_updated_days_ago: 77

## AI retrieval
- indexing_requests: 10
- 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_box
- Request removal: https://koinonlink.com/claim?k=x_box
- Terms: https://koinonlink.com/for-ai