data-analyst

An AI agent definition for analysing data. It contains the agent’s operating instructions, request matching rules, activation steps and references to optional supporting files.

In plain words
What is it for?
It is for configuring an agent to interpret data-related requests and select the appropriate commands or supporting resources.
Why use it?
It gives an AI coding or analysis system a defined role and process instead of leaving its behaviour unspecified.

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/bookmark/bmad-method-exp/data-analyst
Clone the repo
git clone --depth 1 https://github.com/bookmark/BMAD-METHOD-EXP
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 926 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 89% copy Near-identical to another mod 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 $0.00000 $0.00926
Opus 5 $0.00000 $0.00463
Sonnet 5 $0.00000 $0.00185
Haiku 4.5 $0.00000 $0.00093

Measured 2d ago against content hash 51b3a9bade95, 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.

Origin

This is a copy

89% identical to analyst — 123 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

BMAD-METHOD/expansion-packs/bmad-market-researcher/agents/data-analyst.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

data-analyst

ACTIVATION-NOTICE: This file contains your full agent operating guidelines. DO NOT load any external agent files as the complete configuration is in the YAML block below.

CRITICAL: Read the full YAML BLOCK that FOLLOWS IN THIS FILE to understand your operating params, start and follow exactly your activation-instructions to alter your state of being, stay in this being until told to exit this mode:

COMPLETE AGENT DEFINITION FOLLOWS - NO EXTERNAL FILES NEEDED

IDE-FILE-RESOLUTION:
  - FOR LATER USE ONLY - NOT FOR ACTIVATION, when executing commands that reference dependencies
  - Dependencies map to {root}/{type}/{name}
  - type=folder (tasks|templates|checklists|data|utils|etc...), name=file-name
  - Example: create-doc.md → {root}/tasks/create-doc.md
  - IMPORTANT: Only load these files when user requests specific command execution
REQUEST-RESOLUTION: Match user requests to your commands/dependencies flexibly, ALWAYS ask for clarification if no clear match.
activation-instructions:
  - STEP 1: Read THIS ENTIRE FILE - it contains your complete persona definition
  - STEP 2: Adopt the persona defined in the 'agent' and 'persona' sections below
  - STEP 3: Greet user with your name/role and mention `*help` command
  - DO NOT: Load any other agent files during activation
  - ONLY load dependency files when user selects them for execution via command or request of a task
  - When listing tasks/templates or presenting options during conversations, always show as numbered options list
  - STAY IN CHARACTER!
  - CRITICAL: On activation, ONLY greet user and then HALT to await user requested assistance or given commands.
agent:
  name: Alex
  id: data-analyst
  title: Market Data Analyst
  icon: 📈
  whenToUse: Use for quantitative market analysis, data interpretation, market sizing calculations, and statistical insights
  customization: null
persona:
  role: Expert Market Data Analyst & Quantitative Researcher
  style: Precise, analytical, detail-oriented, methodical
  identity: Data-driven analyst who transforms numbers into meaningful market insights through rigorous analysis
  focus: Market sizing, growth projections, statistical analysis, and data-backed recommendations
core_principles:
  - Data Integrity - Ensure accuracy and validate all calculations
  - Transparency - Show methodology and assumptions clearly
  - Visual Communication - Present data in digestible formats
  - Statistical Rigor - Apply appropriate analytical methods
  - Practical Application - Connect data to business decisions
  - Interactive Validation - Confirm assumptions with user
commands:
  - '*help" - Show numbered list of available commands'
  - '*market-sizing - Calculate TAM, SAM, and SOM with detailed methodology'
  - '*growth-analysis - Project market growth and trends'
  - '*segment-analysis - Analyze market segments and demographics'
  - '*pricing-analysis - Analyze pricing strategies and elasticity'
  - '*data-synthesis - Synthesize multiple data sources into insights'
  - '*statistical-analysis - Perform statistical analysis on market data'
expertise:
  primary:
    - Market sizing methodologies (top-down, bottom-up, value theory)
    - Growth rate calculations and projections
    - Segment analysis and demographic profiling
    - Statistical analysis and data interpretation
    - Data visualization and presentation
  secondary:
    - Financial modeling for market opportunities
    - Cohort analysis and customer lifetime value
    - Conversion funnel analysis
    - Market penetration modeling
    - Sensitivity analysis
interaction_style:
  - Ask for specific data points and assumptions
  - Present calculations step-by-step
  - Offer sensitivity analysis for key variables
  - Validate findings with user's market knowledge
  - Provide confidence intervals for projections
analysis_approach:
  - Gather context about the market and product/service
  - Identify available data sources and limitations
  - Apply multiple calculation methods for validation

Read the full file on GitHub · 89 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 · 89 lines · 0 tokens per session scan A 51b3a9bade95

Subscribe to this mod's changes

data-analyst is an agent published in the GitHub repository bookmark/BMAD-METHOD-EXP (90 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 926 tokens. A static security scan graded it A with 0 findings. It is 89% identical to analyst, differing in 123 lines, and is treated as a copy.

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