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format-adapter-jsonl
Convert canonical training examples to JSONL format for training frameworks
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Convert canonical training examples to JSONL format for training frameworks
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Generate Datasheet, Model Card, and Data Statement from a dataset manifest
Deterministically rebuild a dataset from its manifest and verify fixity equivalence
Create a versioned training dataset with manifest, fixity, provenance, and archive snapshot
End-to-end training dataset pipeline — acquire sources through publication
Detect training-eval overlap against benchmark sets before dataset publication
Generate SFT training examples from raw sources using Self-Instruct / Evol-Instruct / SQuAD / STaR patterns
| name | format-adapter-jsonl |
| description | Convert canonical training examples to JSONL format for training frameworks |
| namespace | training-complete |
| category | format |
| platforms | ["claude","copilot","cursor","factory","windsurf","warp","codex","opencode","openclaw","hermes"] |
| commandHint | {"argumentHint":"<input-glob> [--output <path>] [--validate-round-trip]"} |
The identity adapter. Emit canonical training example records (@agentic/code/frameworks/training-complete/schemas/example-record.yaml) as one-record-per-line JSONL with schema validation. This is the reference serialization for canonical form and the source format consumed by the Parquet adapter.
format-adapter-parquet<input-glob> (required) — glob of canonical records--output <path> (optional) — default: .aiwg/training/exports/canonical-<timestamp>.jsonl--validate-round-trip (optional) — reload output and verify byte-level (or structural) equivalenceOne canonical JSON object per line — no transformation, no field dropping:
{"id": "550e8400-...", "task_type": "instruction_following", "input": {"system": "...", "user": "..."}, "output": {"assistant": "..."}, "metadata": {"quality_grade": "HIGH", "license": "CC-BY-4.0", "provenance_id": "prov-...", "created_at": "2026-04-15T01:00:00Z"}}
example-record.yaml.example-record.yaml validation rules.--validate-round-trip) — reparse output and assert structural equality with input.format-convert event with adapter: jsonl and lossless: true.All fields round-trip. Zero loss. This adapter is the benchmark against which other adapters' invariant preservation is measured.
Not required — JSONL preserves the full canonical record. A sidecar is emitted only when callers explicitly request per-line indexing (<output>.index.yaml mapping line numbers to record IDs for random access).
--validate-round-trip succeeds with 100% structural equality.round_trip_invariants from example-record.yaml are preserved verbatim.format-convert event logged with lossless: true.@agentic/code/frameworks/training-complete/schemas/example-record.yaml — source-of-truth schema@agentic/code/addons/semantic-memory/skills/memory-log-append/SKILL.md — logging the format-convert event