synthetic-data-generation skillA
synthetic-data-generation is agent-read markdown (skill) from jnpiyush/agentx: Generate synthetic data for fine-tuning, eval-set bootstrapping, RAG corpus augmentation, and rare-case coverage. Covers Self-Instruct, Evol-Instruct, persona-based generation, distillation from larger models, dataset curation (filtering, dedup, decontamination), and provenance / dataset cards..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Synthetic Data Generation > **Purpose**: Build training and eval datasets quickly without violating user privacy, while controlling for quality, diversity, and contamination. --- ## When to Use This Skill - Bootstrapping eval sets when you have no real labeled data - Augmenting fine-tuning data for under-represented intents / slices - Generating adversarial test cases (combine with `ai-safety-and-red-teaming`) - Creating QA pairs over a private RAG corpus - Privacy-safe substitutes for production data in dev/test ## When NOT to Use - If real, well-labeled data exists at sufficient scale -- use it - For final benchmark numbers in regulated decisions -- use human-labeled holdouts --- ## Common Techniques | Technique | Use For | |-----------|---------| | **Self-Instruct** | Generate instruction/response pairs from a small seed | | **Evol-Instruct** | Iteratively rewrite prompts to be deeper, broader, harder | | **Persona-based** | Generate from N personas to enforce demographic / role diversity | | **Distillation** | Strong-model answers used to train smaller model (check provider terms) | | **Back-translation** | Multilingual coverage | …
Read the whole file at its exact version.
How to install
mdr add jnpiyush/agentx/synthetic-data-generation@v1.0.0mdr add jnpiyush/agentx/synthetic-data-generation@sha256:5d14c8a303fe50a4Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_ccj7k3cwcntxohbo)
1 badge views in 30 days
Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2026-09-15 | f17c505 | 4,909 B | A | view · diff |
| v1.0.0 | 2026-04-30 | 4f38ce8 | 4,907 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4909 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jnpiyush/agentx · 16 stars · license Apache-2.0 · pushed 2026-09-21 · branch master
API
GET https://markdownregistry.com/api/v1/artifacts/art_ccj7k3cwcntxohbo GET https://markdownregistry.com/api/v1/resolve?ref=jnpiyush/agentx/synthetic-data-generation GET https://markdownregistry.com/api/v1/blob/5d14c8a303fe50a43aa74f38252139bd81994f0651b39cf8498c6f5180b92b22
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