Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/JansenAnalytics/claudexnpx agentmods add skills/jansenanalytics/claudex/seed-dataWrote 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/skills/jansenanalytics/claudex/seed-data)<a href="https://agentmods.dev/skills/jansenanalytics/claudex/seed-data"><img src="https://agentmods.dev/badge/skills/jansenanalytics/claudex/seed-data.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.00562 |
| Opus 5 | $0.00013 | $0.00281 |
| Sonnet 5 | $0.00005 | $0.00112 |
| Haiku 4.5 | $0.00003 | $0.00056 |
Grade A, and why
seed-data 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 4d 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
seed-data
Generate realistic test and seed data for any database schema: users, products, orders, time series, financial data.
When to Use
- Populating databases for testing
- Creating demo data
- Generating fixtures for development
- Seeding development environments
- Creating realistic datasets for UI development
Scripts
seed-gen.py
Universal seed data generator with zero dependencies.
python3 scripts/seed-gen.py --schema schema.json --format sql --output seed.sql
python3 scripts/seed-gen.py --schema schema.json --format json
python3 scripts/seed-gen.py --schema schema.json --format csv --output data.csv
Schema format:
{
"tables": [
{
"name": "users",
"count": 100,
"columns": [
{ "name": "id", "type": "serial" },
{ "name": "email", "type": "email" },
{ "name": "name", "type": "name" },
{ "name": "created_at", "type": "datetime", "range": ["2024-01-01", "2024-12-31"] }
]
}
]
}
Supported types: serial, uuid, name, email, phone, address, company, text, integer, float, boolean, datetime, date, choice, foreign_key
timeseries-gen.py
Generate realistic time series data.
python3 scripts/timeseries-gen.py --type stock --start 2024-01-01 --end 2024-12-31 --interval 1h
python3 scripts/timeseries-gen.py --type temperature --start 2024-01-01 --end 2024-12-31 --interval 1d
python3 scripts/timeseries-gen.py --type pageviews --interval 1h --output views.csv
Types: stock, temperature, pageviews, sensor
schema-to-seed.sh
Generate seed schema JSON from existing database.
bash scripts/schema-to-seed.sh --db myapp.db --type sqlite --output schema.json
bash scripts/schema-to-seed.sh --db "postgresql://user:pass@host/db" --type postgres --output schema.json
References
data-patterns.md— Realistic data patterns and distributions
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.
- 4d ago First seen · 78 lines · 26 tokens per session scan A 63708a42ef1f
seed-data is a skill published in the GitHub repository JansenAnalytics/claudex (5 stars, last pushed 2mo ago), licensed MIT. It adds 26 tokens to every session and 562 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 2026-09-03.
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