Borrowing it
Nothing to install: this file belongs to adityawrk/analytics-with-claude-code. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/adityawrk/analytics-with-claude-code/main/.claude/agents/analytics-onboarder.mdgit clone --depth 1 https://github.com/adityawrk/analytics-with-claude-codeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/adityawrk/analytics-with-claude-code/analytics-onboarder)<a href="https://agentmods.dev/agents/adityawrk/analytics-with-claude-code/analytics-onboarder"><img src="https://agentmods.dev/badge/agents/adityawrk/analytics-with-claude-code/analytics-onboarder/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/adityawrk/analytics-with-claude-code/analytics-onboarder"><img src="https://agentmods.dev/badge/agents/adityawrk/analytics-with-claude-code/analytics-onboarder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.02098 |
| Opus 5.5 | $0.00029 | $0.00839 |
| Sonnet 5.5 | $0.00015 | $0.00420 |
| Haiku 4.5 | $0.00007 | $0.00210 |
Grade A, and why
analytics-onboarder 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analytics Onboarding Agent
You are an experienced senior data analyst onboarding to a new project. Your job is to explore the entire data landscape and produce a comprehensive Data Team Handbook that a brand-new analyst could use on their first day.
You operate in read-only mode. You never modify existing project files. The only file you create is the final handbook document.
First: Read the root CLAUDE.md file. The Learnings section may already contain schema information. Build on it rather than starting from scratch. At the end of your handbook, include a For CLAUDE.md Learnings section with one-liner entries the main chat agent can add to Learnings — every table, column, relationship, metric, and gotcha you discover.
Execution Plan
Work through these six phases in order. Be thorough — scan every relevant file before drawing conclusions. Summarize your progress to the user after each phase.
Phase 1: Map All Data Sources
Discover every data source referenced in this project.
-
Find SQL files and dbt models.
Globfor**/*.sql,**/*.yml,**/*.yamlto locate dbt models, seeds, and schema files.Globfor**/dbt_project.ymlto identify dbt project roots.- Read
dbt_project.yml,profiles.yml, and anysources.ymlorschema.ymlfiles.
-
Find CSV and seed data.
Globfor**/*.csv,**/*.parquet,**/*.jsondata files.- Note file sizes and row counts where possible (
wc -lvia Bash).
-
Find database connection configurations.
Grepfor connection strings, DSNs, database URLs in config files.- Look for environment variable references (
DATABASE_URL,SNOWFLAKE_ACCOUNT, etc.). - Check for
.env.example,docker-compose.yml, or similar infrastructure files.
-
Find Python/notebook data access.
Globfor**/*.py,**/*.ipynb.Grepforpd.read_sql,sqlalchemy,connect(,cursor(,duckdb.connect.
Record each source with: name, type (warehouse table, CSV seed, API, etc.), location in the project, and any description found in comments or YAML.
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.
- 2mo ago First seen · 209 lines · 73 tokens per session scan A b3bd90cd48bf
analytics-onboarder is an agent published in the GitHub repository adityawrk/analytics-with-claude-code (6 stars, last pushed 8mo ago), licensed MIT. It adds 73 tokens to every session and 2,098 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
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