{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:HVIJJEPK5CPRZ3KZ6OJGCOJFES","short_pith_number":"pith:HVIJJEPK","schema_version":"1.0","canonical_sha256":"3d509491eae89f1ced59f39261392524b99f21da954bea20909d5497a56a0a66","source":{"kind":"arxiv","id":"2302.11382","version":1},"attestation_state":"computed","paper":{"title":"A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"A catalog of prompt patterns provides reusable solutions to common problems in LLM conversations.","cross_cats":["cs.AI"],"primary_cat":"cs.SE","authors_text":"Ashraf Elnashar, Carlos Olea, Douglas C. Schmidt, Henry Gilbert, Jesse Spencer-Smith, Jules White, Michael Sandborn, Quchen Fu, Sam Hays","submitted_at":"2023-02-21T12:42:44Z","abstract_excerpt":"Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LLM to enforce rules, automate processes, and ensure specific qualities (and quantities) of generated output. Prompts are also a form of programming that can customize the outputs and interactions with an LLM. This paper describes a catalog of prompt engineering techniques presented in pattern form that have been applied to solve common problems when conversing with LLMs. Prompt patterns are a knowledge transfer method"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":true,"formal_links_present":true},"canonical_record":{"source":{"id":"2302.11382","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-02-21T12:42:44Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b44d01d7659f193801c93a5aa46218863a5e304ef4147afd8ed96ebcb97bb77f","abstract_canon_sha256":"0bab6574f91d4872e4416cba8bef95b65278b4b9517ecbc312269aa752763dac"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:38:53.175131Z","signature_b64":"G8jCbQGouvvtu7HPIy94geB5xM0K37e6b3+L6AyCli/MB+nTNIxcRaVf7Wl8UXNd/nXs6agvWuk4v4kqIIRRDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3d509491eae89f1ced59f39261392524b99f21da954bea20909d5497a56a0a66","last_reissued_at":"2026-05-17T23:38:53.174528Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:38:53.174528Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"A catalog of prompt patterns provides reusable solutions to common problems in LLM conversations.","cross_cats":["cs.AI"],"primary_cat":"cs.SE","authors_text":"Ashraf Elnashar, Carlos Olea, Douglas C. Schmidt, Henry Gilbert, Jesse Spencer-Smith, Jules White, Michael Sandborn, Quchen Fu, Sam Hays","submitted_at":"2023-02-21T12:42:44Z","abstract_excerpt":"Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LLM to enforce rules, automate processes, and ensure specific qualities (and quantities) of generated output. Prompts are also a form of programming that can customize the outputs and interactions with an LLM. This paper describes a catalog of prompt engineering techniques presented in pattern form that have been applied to solve common problems when conversing with LLMs. Prompt patterns are a knowledge transfer method"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"This paper provides a catalog of patterns that have been applied successfully to improve the outputs of LLM conversations.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The patterns described are generalizable and can be adapted to different domains and LLMs beyond the specific examples provided in the paper.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"The authors present a catalog of prompt patterns that provide reusable solutions to common problems in generating and interacting with outputs from LLMs.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"A catalog of prompt patterns provides reusable solutions to common problems in LLM conversations.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"2552854c45838fae58ae92c1768dddb8c20ab203daa62a62796195aabe8e4d95"},"source":{"id":"2302.11382","kind":"arxiv","version":1},"verdict":{"id":"34690b2f-f55c-4f3e-a2cc-84403b3b99c0","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-15T07:04:31.897769Z","strongest_claim":"This paper provides a catalog of patterns that have been applied successfully to improve the outputs of LLM conversations.","one_line_summary":"The authors present a catalog of prompt patterns that provide reusable solutions to common problems in generating and interacting with outputs from LLMs.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The patterns described are generalizable and can be adapted to different domains and LLMs beyond the specific examples provided in the paper.","pith_extraction_headline":"A catalog of prompt patterns provides reusable solutions to common problems in LLM conversations."},"references":{"count":38,"sample":[{"doi":"","year":2021,"title":"On the Opportunities and Risks of Foundation Models","work_id":"a18039e9-928d-47c9-a836-32656a71bf71","ref_index":1,"cited_arxiv_id":"2108.07258","is_internal_anchor":true},{"doi":"","year":2023,"title":"A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","work_id":"41dff74c-00b2-4c77-a674-9f86030c06c8","ref_index":2,"cited_arxiv_id":"2302.04023","is_internal_anchor":true},{"doi":"","year":2022,"title":"How well does chatgpt do when taking the med ical licensing exams?","work_id":"3c45ec04-99b1-4d7d-9204-54c83d9c27b5","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2022,"title":"Architecting the future of software engi neering,","work_id":"840e0290-70ed-45ad-942d-544646219a5d","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"Github copilot · your ai pair programmer","work_id":"e6d22292-c09d-41bf-8217-9c08281d81dd","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":38,"snapshot_sha256":"0482ea9a7cd9bcd01764164ac8fcb4a629cc036b7556510cac7317678c016486","internal_anchors":6},"formal_canon":{"evidence_count":2,"snapshot_sha256":"d0b34ebdd5105c131c24bf198b891e7f1df76c397f415730b6b146384a464df7"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2302.11382","created_at":"2026-05-17T23:38:53.174613+00:00"},{"alias_kind":"arxiv_version","alias_value":"2302.11382v1","created_at":"2026-05-17T23:38:53.174613+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.11382","created_at":"2026-05-17T23:38:53.174613+00:00"},{"alias_kind":"pith_short_12","alias_value":"HVIJJEPK5CPR","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_16","alias_value":"HVIJJEPK5CPRZ3KZ","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_8","alias_value":"HVIJJEPK","created_at":"2026-05-18T12:33:33.725879+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":38,"internal_anchor_count":38,"sample":[{"citing_arxiv_id":"2312.03853","citing_title":"Dr. Jekyll and Mr. Hyde: Two Faces of LLMs","ref_index":21,"is_internal_anchor":true},{"citing_arxiv_id":"2405.18179","citing_title":"Rethinking the A in STEAM: Insights from and for AI Literacy Education","ref_index":57,"is_internal_anchor":true},{"citing_arxiv_id":"2410.01026","citing_title":"Understanding the Human-LLM Dynamic: A Literature Survey of LLM Use in Programming Tasks","ref_index":104,"is_internal_anchor":true},{"citing_arxiv_id":"2504.19959","citing_title":"From Concept to Practice: an Automated LLM-aided UVM Machine for RTL Verification","ref_index":37,"is_internal_anchor":true},{"citing_arxiv_id":"2505.07700","citing_title":"PatchTrack: A Comprehensive Analysis of ChatGPT's Influence on Pull Request Outcomes","ref_index":30,"is_internal_anchor":true},{"citing_arxiv_id":"2604.15343","citing_title":"When the Loop Closes: Architectural Limits of In-Context Isolation, Metacognitive Co-option, and the Two-Target Design Problem in Human-LLM Systems","ref_index":32,"is_internal_anchor":true},{"citing_arxiv_id":"2605.15865","citing_title":"From Text to DSL: Evaluating Grammar-Based Model Generation Using Open LLMs","ref_index":1,"is_internal_anchor":true},{"citing_arxiv_id":"2605.16538","citing_title":"LLMs in Qualitative Research: Opportunities, Limitations, and Practical Considerations","ref_index":59,"is_internal_anchor":true},{"citing_arxiv_id":"2605.17152","citing_title":"Multilingual and Multimodal LLMs in the Wild: Building for Low-Resource Languages","ref_index":221,"is_internal_anchor":true},{"citing_arxiv_id":"2605.19035","citing_title":"Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On","ref_index":64,"is_internal_anchor":true},{"citing_arxiv_id":"2605.17857","citing_title":"Towards SocratiCode: Designing a Generative AI-Based Programming Tutor for K-12 Students through a 4-Week Participatory Design Study","ref_index":35,"is_internal_anchor":true},{"citing_arxiv_id":"2605.19940","citing_title":"Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains","ref_index":49,"is_internal_anchor":true},{"citing_arxiv_id":"2506.16345","citing_title":"Can GPT-4o Evaluate Usability Like Human Experts? A Comparative Study on Issue Identification in Heuristic Evaluation","ref_index":49,"is_internal_anchor":true},{"citing_arxiv_id":"2510.23883","citing_title":"Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges","ref_index":56,"is_internal_anchor":true},{"citing_arxiv_id":"2310.11324","citing_title":"Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting","ref_index":64,"is_internal_anchor":true},{"citing_arxiv_id":"2601.11848","citing_title":"Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI","ref_index":80,"is_internal_anchor":true},{"citing_arxiv_id":"2603.03295","citing_title":"Language Model Goal Selection Differs from Humans' in a Self-Directed Learning Task","ref_index":20,"is_internal_anchor":true},{"citing_arxiv_id":"2604.15343","citing_title":"When the Loop Closes: Architectural Limits of In-Context Isolation, Metacognitive Co-option, and the Two-Target Design Problem in Human-LLM Systems","ref_index":32,"is_internal_anchor":true},{"citing_arxiv_id":"2408.08435","citing_title":"Automated Design of Agentic Systems","ref_index":29,"is_internal_anchor":true},{"citing_arxiv_id":"2605.14312","citing_title":"Making OpenAPI Documentation Agent-Ready: Detecting Documentation and REST Smells with a Multi-Agent LLM System","ref_index":24,"is_internal_anchor":true},{"citing_arxiv_id":"2602.20867","citing_title":"SoK: Agentic Skills -- Beyond Tool Use in LLM Agents","ref_index":27,"is_internal_anchor":true},{"citing_arxiv_id":"2605.12657","citing_title":"User Reviews as a Source for Usability Requirements: A Precursor Study on Using Large Language Models","ref_index":14,"is_internal_anchor":true},{"citing_arxiv_id":"2605.13280","citing_title":"The Readability Spectrum: Patterns, Issues, and Prompt Effects in LLM-Generated Code","ref_index":102,"is_internal_anchor":true},{"citing_arxiv_id":"2604.14197","citing_title":"The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure","ref_index":13,"is_internal_anchor":true},{"citing_arxiv_id":"2604.04990","citing_title":"Architecture Without Architects: How AI Coding Agents Shape Software Architecture","ref_index":10,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":2,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES","json":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES.json","graph_json":"https://pith.science/api/pith-number/HVIJJEPK5CPRZ3KZ6OJGCOJFES/graph.json","events_json":"https://pith.science/api/pith-number/HVIJJEPK5CPRZ3KZ6OJGCOJFES/events.json","paper":"https://pith.science/paper/HVIJJEPK"},"agent_actions":{"view_html":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES","download_json":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES.json","view_paper":"https://pith.science/paper/HVIJJEPK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2302.11382&json=true","fetch_graph":"https://pith.science/api/pith-number/HVIJJEPK5CPRZ3KZ6OJGCOJFES/graph.json","fetch_events":"https://pith.science/api/pith-number/HVIJJEPK5CPRZ3KZ6OJGCOJFES/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES/action/storage_attestation","attest_author":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES/action/author_attestation","sign_citation":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES/action/citation_signature","submit_replication":"https://pith.science/pith/HVIJJEPK5CPRZ3KZ6OJGCOJFES/action/replication_record"}},"created_at":"2026-05-17T23:38:53.174613+00:00","updated_at":"2026-05-17T23:38:53.174613+00:00"}