Borrowing it
Nothing to install: this file belongs to newfront/pyspark-datagen. 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/newfront/pyspark-datagen/main/.agents/skills/add-datagen-generator/SKILL.mdgit clone --depth 1 https://github.com/newfront/pyspark-datagenWrote 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/newfront/pyspark-datagen/add-datagen-generator)<a href="https://agentmods.dev/skills/newfront/pyspark-datagen/add-datagen-generator"><img src="https://agentmods.dev/badge/skills/newfront/pyspark-datagen/add-datagen-generator/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/skills/newfront/pyspark-datagen/add-datagen-generator"><img src="https://agentmods.dev/badge/skills/newfront/pyspark-datagen/add-datagen-generator.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 | $0.00074 | $0.01286 |
| Opus 5 | $0.00037 | $0.00643 |
| Sonnet 5 | $0.00015 | $0.00257 |
| Haiku 4.5 | $0.00007 | $0.00129 |
Grade A, and why
add-datagen-generator 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 10d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add a New Data Generator
Use this skill when adding a new message type and generator to learning-spark-datagen/ (proto + Python generator + CLI + tests). Follow the existing User and Order generators as the reference pattern.
1. Proto and validation
- Add
protos/<domain>/v1/<message>.proto(e.g.order/v1/order.proto). - Use
buf.validateso every generated message passesprotovalidate.validate(message):- IDs / FKs:
(buf.validate.field).string.uuid = trueand(buf.validate.field).required = truefor string IDs that link to other entities. - Required fields:
(buf.validate.field).required = trueon message fields and on scalars where zero is invalid. - Nested messages:
required = trueon any message field that must be set (e.g.total,unit_cost). - Strings:
(buf.validate.field).string = { min_len: 1 }for non-empty (e.g.currency). - Repeated:
(buf.validate.field).repeated = { min_items: 1 }when at least one item is required. - Numbers: e.g.
(buf.validate.field).uint32 = { gte: 1 }for counts.
- IDs / FKs:
- Import
buf/validate/validate.protoand keepsyntax = "proto3"and package/options consistent with existing protos.
2. Generate and package layout
- Run
buf generate(ormake build) from the project root sogen/python/<domain>/v1/<message>_pb2.pyis created. - If a new top-level package is created under
gen/python/, add__init__.pyin each directory (e.g.gen/python/order/__init__.py,gen/python/order/v1/__init__.py) sofrom order.v1 import order_pb2works.
3. Generator class
- Add
src/learning_spark_datagen/datagen/gen_<name>.py(e.g.gen_order.py). - Mirror the structure of
GenUser/GenOrder:__init__(self, seed, <parent_ids>=None)— e.g.user_idsso child records can reference parent UUIDs.generate_one(self, index)— deterministic fromseed + index(same index ⇒ same message). UseRandom(seed + index)and a fixed pool of IDs (e.g. product UUIDs) when you need deterministic sub-messages.generate(self, count)— return[self.generate_one(i) for i in range(count)].@staticmethod to_dict(msg),write_ndjson(path, messages),read_ndjson(path)usingjson_format.MessageToDict/ParseDictandpreserving_proto_field_name=True.
- If the message has a parent link (e.g.
user_id), accept an optional list of parent IDs and assignparent_ids[index % len(parent_ids)](or generate deterministic UUIDs when the list is not provided). - Ensure every generated message passes
protovalidate.validate(message)(required fields set, UUIDs valid, min_items satisfied, etc.).
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.
- 10d ago First seen · 66 lines · 74 tokens per session scan A c31db573511e
add-datagen-generator is a skill published in the GitHub repository newfront/pyspark-datagen (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 74 tokens to every session and 1,286 once invoked, about $0.0004 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 2026-08-31.
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