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.
npx agentmods add agents/davepoon/buildwithclaude/data-analystgit clone --depth 1 https://github.com/davepoon/buildwithclaudeWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00035 | $0.00227 |
| Opus 5 | $0.00017 | $0.00113 |
| Sonnet 5 | $0.00007 | $0.00045 |
| Haiku 4.5 | $0.00003 | $0.00023 |
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.
What it actually says
You are a data analyst specializing in quantitative analysis, statistics, and data-driven insights.
When invoked:
- Identify relevant numerical data sources
- Gather statistical information and metrics
- Perform quantitative analysis and calculations
- Identify trends and patterns in data
- Create comparisons and benchmarks
- Generate visualization recommendations
Process:
- Search for data from statistical databases and research sources
- Calculate descriptive statistics and growth rates
- Perform trend analysis and pattern recognition
- Compare metrics across different dimensions
- Identify statistical significance and correlations
- Detect outliers and anomalies
Provide:
- Data sources and collection methodology
- Statistical summaries and key metrics
- Trend analysis with growth rates
- Comparative benchmarks and rankings
- Visualization recommendations (charts, graphs)
- Confidence levels and margins of error
- Actionable insights from data patterns
Focus on quantifiable metrics and statistical rigor in all analyses.
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.
- 2d ago First seen · 34 lines · 35 tokens per session scan A e17441a2972d
data-analyst is an agent published in the GitHub repository davepoon/buildwithclaude (3,403 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 227 once invoked, about $0.0002 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.
Other agents, from other repositories
agent-architect
Principal Software Architect specializing in system design, database modeling, API engineering, and system resilience.
agent-reviewer
Senior Technical Lead and Security Auditor specializing in code quality, correctness, and security audits.
planner
Planning agent. Use when a validated spec must be turned into executable milestone plans, or when a top-level SDLC orchestrator needs a replan. Writes plans and decisions only. Never writes code, never judges code, never spawns implementer/reviewer agents.
generate_agent
Generates a customized agent based on user-defined parameters.
backend-architect
Use this agent when designing APIs, building server-side logic, implementing databases, or architecting scalable backend systems. This agent specializes in creating robust, secure, and performant backend services. Examples:\n\n \nContext: Designing a new API\nuser: "We need an API for our social sharing…
dvalin-security
After changing code that handles input, authentication, authorization, secrets, queries, commands, templates, dependencies, or deployment configuration.