메뉴
Web app for creating, editing, and validating JSONL fine-tuning datasets. Checks format compliance for OpenAI, Anthropic, and Llama formats, detects duplicates, scores quality, and exports clean datasets.
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
| name | finetune-data-curator |
| description | Web app for creating, editing, and validating JSONL fine-tuning datasets. Checks format compliance for OpenAI, Anthropic, and Llama formats, detects duplicates, scores quality, and exports clean datasets. |
| triggers | ["fine-tune dataset","jsonl curator","training data","finetune data","dataset quality","llm training dataset","jsonl validation"] |
Use this skill when you need to:
cd finetune-data-curator
cp .env.example .env
# edit .env: set ADMIN_KEY=<secure random string> and DATA_DIR=./data
pnpm install
pnpm dev # server + SPA on :4400
Open http://localhost:4400.
ADMIN_KEY=mysecretkey docker compose up
# App: http://localhost:4400
Via the web UI: click "New Dataset", choose a format (OpenAI, Anthropic, or Llama), name it.
Via API:
curl -X POST http://localhost:4400/api/datasets \
-H "X-Admin-Key: $ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{"name": "my-dataset", "format": "openai"}'
Via the web UI: open a dataset, click Import, paste JSONL or upload a file.
Via API:
curl -X POST http://localhost:4400/api/datasets/ds_abc/samples \
-H "X-Admin-Key: $ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '[{"messages": [{"role": "user", "content": "Hello"}, {"role": "assistant", "content": "Hi!"}]}]'
Via the web UI: open a dataset, click "Run Validation".
Via API:
curl -X POST http://localhost:4400/api/datasets/ds_abc/validate \
-H "X-Admin-Key: $ADMIN_KEY"
Validation checks: format compliance, missing fields, empty content, excessive length, degenerate samples.
curl -X POST http://localhost:4400/api/datasets/ds_abc/dedup \
-H "X-Admin-Key: $ADMIN_KEY"
Returns pairs with Jaccard similarity above the configured threshold (default 0.8).
curl -X POST http://localhost:4400/api/datasets/ds_abc/split \
-H "X-Admin-Key: $ADMIN_KEY" \
-H "Content-Type: application/json" \
-d '{"ratio": 0.8, "seed": 42}'
Creates ds_abc.train.jsonl (80%) and ds_abc.eval.jsonl (20%).
# Download as OpenAI format
curl "http://localhost:4400/api/datasets/ds_abc/export?format=openai" \
-H "X-Admin-Key: $ADMIN_KEY" \
-o my-dataset.jsonl
# Convert to Anthropic format on export
curl "http://localhost:4400/api/datasets/ds_abc/export?format=anthropic" \
-H "X-Admin-Key: $ADMIN_KEY" \
-o my-dataset-anthropic.jsonl
# Export train split only
curl "http://localhost:4400/api/datasets/ds_abc/export?format=openai&split=train" \
-H "X-Admin-Key: $ADMIN_KEY" \
-o train.jsonl
| Variable | Default | Description |
|---|---|---|
PORT | 4400 | Server listen port |
DATA_DIR | ./data | Directory for JSONL files and index.json |
ADMIN_KEY | (required) | Header value required for write operations |
MAX_UPLOAD_MB | 50 | Maximum upload file size |
Edit the visual grid layout of a garden bed, assigning crops to cells on a canvas editor. Use when asked to arrange crops in a bed, draw a planting layout, move crops around, visualize companion planting placement, or check for enemy crop adjacency in a specific bed. Triggers include "layout editor", "bed grid", "draw the bed", "assign crops to cells", "companion warning in layout", or similar visual planning tasks.
Plan crop rotations, planting schedules, and companion planting for garden beds and fields. Use when asked to manage a farm, garden, or plot layout; schedule what to plant and when; check companion planting relationships; track rotation history; or generate a printable planting schedule. Triggers include "crop rotation", "planting schedule", "companion planting", "garden bed", "what to plant", "frost dates", or any task involving seasonal crop planning.
Log crop harvests with yield quantity, quality grade, field, and storage destination. Use when asked to record a harvest, check total yield for a crop or field, filter harvest history by date or grade, view analytics charts, or export harvest data. Triggers include "log harvest", "record yield", "harvest entry", "crop yield", "grade breakdown", "field yield", "harvest history", or any task involving tracking what was picked and where it went.
Query and interpret yield analytics data from harvest-logger. Use when asked about yield trends over time, comparing crop performance, finding the best-performing field, analyzing grade quality rates, running season comparisons, or generating data for external reports. Triggers include "yield trend", "top crops", "grade analysis", "field performance", "season comparison", "best yield", "harvest analytics", or any task requiring aggregated harvest data rather than individual entries.
Schedule and monitor irrigation zones with weather-aware skip rules and water usage tracking. Use when asked to manage irrigation timing, set up zone schedules, configure rain-based skip rules, check water usage, trigger manual watering, or apply seasonal duration presets. Triggers include "irrigation", "sprinkler schedule", "watering zones", "skip when raining", "water usage tracking", "manual run irrigation", or any task involving automated watering management.
Configure and troubleshoot weather-based irrigation skip rules using the Open-Meteo API. Use when asked to set up rain forecast skips, configure rain threshold values, debug why zones are or are not being skipped, check weather cache status, understand skip preview results, or tune skip rule sensitivity for your local climate. Triggers include "skip when rain", "weather threshold", "Open-Meteo", "skip preview", "rain forecast rule", "freeze protection", or any task involving weather-driven irrigation decisions.