بنقرة واحدة
format-adapter-jsonl
Convert canonical training examples to JSONL format for training frameworks
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Convert canonical training examples to JSONL format for training frameworks
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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