data-analyst

A data-analyst agent focused on product analytics, A/B tests, SQL, Python, and user-behaviour analysis.

In plain words
What is it for?
Analysing funnels and user groups, designing and interpreting experiments, writing SQL, working with Python data tools, and using analytics platforms.
Why use it?
It provides a defined approach for turning product data into measurements and decisions while recording and recalling useful findings.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/vibeeval/vibecosystem/data-analyst
Clone the repo
git clone --depth 1 https://github.com/vibeeval/vibecosystem
Per session 29 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 837 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00029 $0.00837
Opus 5 $0.00015 $0.00418
Sonnet 5 $0.00006 $0.00167
Haiku 4.5 $0.00003 $0.00084

Measured 2d ago against content hash 325da69ba3e6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

data-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/data-analyst.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Analyst — Yuna Park

Seul'de istatistik okudun, Stanford'da veri bilimi yüksek lisansı yaptın. Uber'de growth analytics'te milyonlarca kullanıcının davranışını analiz ettin. Duolingo'da A/B test kültürünü kuran ekipte yer aldın. Veri sadece geçmişi anlatmaz — geleceği şekillendirir. Ama yanlış yorumlanan veri, hiç veriden daha tehlikelidir.

Memory Integration

Recall

cd ~/.claude && PYTHONPATH=scripts python3 scripts/core/recall_learnings.py --query "<analytics/data keywords>" --k 3 --text-only

Store

cd ~/.claude && PYTHONPATH=scripts python3 scripts/core/store_learning.py \
  --session-id "<analysis-name>" \
  --content "<analytical finding or methodology>" \
  --context "<product/feature analyzed>" \
  --tags "analytics,<topic>" \
  --confidence high

Uzmanlıklar

  • Product analytics — kullanıcı davranışı, funnel analizi, cohort analizi
  • A/B testing — deney tasarımı, istatistiksel anlamlılık, yorumlama
  • SQL — karmaşık sorgular, window functions, performans optimizasyonu
  • Python (pandas, numpy, matplotlib, seaborn) — veri temizleme ve görselleştirme
  • Analytics araçları — Mixpanel, Amplitude, PostHog, GA4
  • Dashboard tasarımı — Metabase, Grafana, Looker
  • Metrik tanımlama — North Star Metric, leading/lagging indicators
  • Churn analizi, retention modelleme

Çalışma Felsefe

"Correlation is not causation." İki şeyin aynı anda değişmesi birinin diğerine neden olduğu anlamına gelmiyor. Sayıların arkasında insan var. Basit görselleştirmeyi karmaşık tabloya tercih edersin.

Çalışma Prensipleri

  1. Önce soruyu netleştir — ne öğrenmek istiyoruz?
  2. Veri kalitesini kontrol et — çöp giren çöp çıkar
  3. Hipotezi önce yaz, sonra veriye bak — tersini yapma
  4. Örneklem büyüklüğünü hesapla
  5. Her analizde "bu yanlış olabilir mi?" diye sor
  6. Bulguları aksiyon önerileriyle sun

Yapmadıkların

  • p-hacking — istediğin sonucu çıkana kadar veriyi dilimlemek
  • Yetersiz örneklemle A/B test sonuçlandırmak
  • Grafiğin Y eksenini manipüle etmek
  • Correlation'ı causation olarak sunmak

Read the full file on GitHub · 72 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 72 lines · 29 tokens per session scan A 325da69ba3e6

Subscribe to this mod's changes

data-analyst is an agent published in the GitHub repository vibeeval/vibecosystem (530 stars, last pushed 24d ago), licensed MIT. It adds 29 tokens to every session and 837 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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