trace-to-training-data SKILL.md skillA
trace-to-training-data from wshobson/agents is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add wshobson/agents/trace-to-training-data@git:20260714.baa5bd7Pins git:20260714.baa5bd7 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- wshobson/agents
- Path
plugins/llm-finetuning/skills/trace-to-training-data/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260714.baa5bd7, committed Jul 14, 2026
- Size
- 6,251 bytes
- Repository stars
- 42,320
- License
- MIT
Convert evaluation traces and production logs into SFT examples and preference pairs. Use when graded traces or failure examples exist and need to become training data, when applying rejection sampling to model outputs, or when building DPO pairs from passing and failing runs.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Trace To Training Data
This skill assumes `eval-harness-first`
already graded the traces being
converted here — goldens, graders,
and `runs/<run-id>/results.json`
all exist before conversion
starts. This is the flywheel edge
that skill names in its own flow:
"the same labeled traces become
the training set." Conversion
happens here; grading already
happened upstream.
**Input:** graded traces —
`eval/goldens.jsonl` plus
`runs/<run-id>/results.json`, each
row carrying a `task_id`, a
`verdict` from the grader, and a
`reward` when the task supports a
scalar score (judge score,
execution partial-credit, or an
RLVR verifier):
```json
{"task_id": "t-042", "trace_id": "t-042-a3",
"messages": [{"role": "user", "content": "..."}],
"verdict": "pass", "reward": 0.91,
"grader": "exact_match"}
```
**Output format:** rows shaped
exactly like `dataset-curation`'s
Format Selection table — SFT
`messages` rows or DPO
`prompt`/`chosen`/`rejected`
pairs — so this skill's output is
that skill's input with no
reshaping step in between.
## The Principle
The eval harness already did the
labeling work: every trace in
`results.json` carries a verdict,
and often a reward, before this
…Read the whole file at its exact version.
How to install
mdr add wshobson/agents/trace-to-training-data@sha256:9f7ec8803b8b10f8The line at the top of this page pins the label git:20260714.baa5bd7, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_s2lz6k4epoaznlg3)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Jul 14, 2026.
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 (6251 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
wshobson/agents · 42,320 stars · license MIT · pushed 2026-11-08 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_s2lz6k4epoaznlg3 GET https://markdownregistry.com/api/v1/resolve?ref=wshobson/agents/trace-to-training-data GET https://markdownregistry.com/api/v1/blob/9f7ec8803b8b10f8ac7f965ea89be62c5006c03420a328782a0a1ae87e42e022
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.