{"version":"1.0","type":"card","id":"97531293-814d-4fc1-a7f3-a71e44ebf553","url":"https://stacklist.com/card/97531293-814d-4fc1-a7f3-a71e44ebf553","title":"22365_3_Prompt Engineering_v7 (1).pdf - Google Drive","source_url":"https://drive.google.com/file/d/1AbaBYbEa_EbPelsT40-vj64L-2IwUJHy/view","note":"Download a PDF file titled 'Prompt Engineering' in version 7, a document probably related to artificial intelligence or language models.","image":{"url":"https://ucarecdn.com/c9f514f3-91d6-4750-9c54-924573a759a1/-/preview/1000x1000","alt":"22365_3_Prompt Engineering_v7 (1).pdf - Google Drive","width":1200,"height":630},"stack":{"id":"42966089-f76b-4adc-8004-00e21e399b0a","title":"useful links","url":"https://stacklist.com/stack/42966089-f76b-4adc-8004-00e21e399b0a"},"created_at":"2025-04-22T18:44:18.567Z","updated_at":null,"aco":{"summary":"This website is a document titled \"Prompt Engineering\" written by Lee Boonstra and dated February 2025. It is a guide on prompt engineering, focusing on techniques like general prompting, one-shot & few-shot prompting, and system, contextual, and role prompting. It also covers LLM output configuration, including output length, sampling controls, temperature, top-K and top-P, and how to put them all together. The document is intended to be informative and provide a comprehensive overview of prompt engineering techniques. \n","tags":[],"key_entities":[],"classification":null,"language":null,"confidence":null,"provenance":null,"token_counts":{"approximate":143},"content_hash":null,"acp_version":"0.2","body_available":false,"body_tokens":0,"visibility":"public","agent_accessible":true,"status":"final"},"_links":{"self":"/api/public/card/97531293-814d-4fc1-a7f3-a71e44ebf553.json","html":"https://stacklist.com/card/97531293-814d-4fc1-a7f3-a71e44ebf553","md":"/api/public/card/97531293-814d-4fc1-a7f3-a71e44ebf553.md","stack_json":"/api/public/stack/42966089-f76b-4adc-8004-00e21e399b0a.json"}}