Split, index, and retrieve internal policy documents and approval workflows.
npx skills add https://github.com/bettercallfan/deerflow --skill policy-rag
Please help me install this Agent Skill. Skill: policy-rag Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/policies-regulations/policy-rag Command: npx skills add https://github.com/bettercallfan/deerflow --skill policy-rag
This Skill addresses the complexity of managing internal policies and approval workflows, allowing for efficient document processing, indexing, and search capabilities within an enterprise environment.
Run the policy-rag skill and upload your policy document to process and index it.
High-intent search queries and answers about installing and using this skill.
This Skill automates policy document indexing by splitting documents into manageable sections and creating searchable indexes for quick clause retrieval. You upload your policy documents to process and index them for enterprise policy management.
Yes, Excel approval tables can be transformed into structured data for easy retrieval. This Skill supports converting Excel approval workflows into a searchable format, enabling efficient approval path search and policy clause retrieval.
Yes, running policy management indexing workflows requires Python3, Dashscope, and Pandas. These dependencies provide the necessary scripts and tools for document parsing, indexing, and search functionality within your enterprise environment.
The best way to search specific policy clauses and approval paths is by indexing split policy documents and converted approval tables. This allows you to quickly retrieve exact clauses and map approval paths based on specific queries.
Yes, this document indexing approach works with both Excel and text policy files. It uses openpyxl and xlrd for Excel approval table conversion, while processing standard policy documents for splitting, indexing, and clause retrieval.
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