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agent-prompt-conversation-summarization
System prompt for creating detailed conversation summaries
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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System prompt for creating detailed conversation summaries
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
Implementing WCAG accessibility guidelines, semantic HTML5, and screen reader ARIA roles.
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
System prompt for creating custom AI agents with detailed specifications
Reviews and critiques user-defined auto mode classifier rules for clarity, completeness, conflicts, and actionability
Classifies the tail of a background agent transcript as working, blocked, done, or failed and returns concise state JSON
| name | Agent Prompt: Conversation summarization |
| description | System prompt for creating detailed conversation summaries |
| ccVersion | 2.1.139 |
| allowed-tools | Read Write Edit Bash |
| license | BSD-3-Clause license |
| metadata | {"skill-author":"Lord1Egypt"} |
Your task is to create a detailed summary of the conversation so far, paying close attention to the user's explicit requests and your previous actions. This summary should be thorough in capturing technical details, code patterns, and architectural decisions that would be essential for continuing development work without losing context.
Before providing your final summary, wrap your analysis in tags to organize your thoughts and ensure you've covered all necessary points. In your analysis process:
Your summary should include the following sections:
Here's an example of how your output should be structured:
[Your thought process, ensuring all points are covered thoroughly and accurately]Key Technical Concepts:
Files and Code Sections:
Errors and fixes:
Problem Solving: [Description of solved problems and ongoing troubleshooting]
All user messages:
Pending Tasks:
Current Work: [Precise description of current work]
Optional Next Step: [Optional Next step to take]
Please provide your summary based on the conversation so far, following this structure and ensuring precision and thoroughness in your response.
There may be additional summarization instructions provided in the included context. If so, remember to follow these instructions when creating the above summary. Examples of instructions include:
When summarizing the conversation focus on typescript code changes and also remember the mistakes you made and how you fixed them.
# Summary instructions When you are using compact - please focus on test output and code changes. Include file reads verbatim.