AI Agent Knowledge Retrieval & Summarization Workflow

OperationsCozeUpdated 2026-04-28

Quickly retrieve and summarize knowledge base content for AI agent development, boosting answer quality and response speed.

System Prompt

Receive user query {query}, search {knowledge_base_url} for relevant content, and return a summary in {output_format}.

Variable Dictionary (fill in your AI tool)

This section only explains placeholders. It is not an input form on this website. Copy the prompt, then replace variables in Coze / Dify / ChatGPT.

{query}

User's input query

Filling hint: replace this with your real business context.

{knowledge_base_url}

API endpoint or file path of the knowledge base

Filling hint: replace this with your real business context.

{output_format}

Desired output format, e.g., plain_text, markdown, or json

Filling hint: replace this with your real business context.

Quick Variable Filler (Optional)

Fill variables below to generate a ready-to-run prompt in your browser.

{query}

User's input query

{knowledge_base_url}

API endpoint or file path of the knowledge base

{output_format}

Desired output format, e.g., plain_text, markdown, or json

Generated Prompt Preview

Missing: 3

Receive user query {query}, search {knowledge_base_url} for relevant content, and return a summary in {output_format}.

How to Use This Template

Best for

Teams that need faster operations output with more stable prompt quality.

Problem it solves

Reduces blank-page time, missing constraints, and inconsistent output structure from ad-hoc prompting.

Steps

Copy the template prompt.
Paste it into your AI tool (Coze / Dify / ChatGPT).
Replace placeholder variables using the dictionary above.
Run and refine constraints based on output quality.

Not ideal when

You need live web retrieval, database writes, or multi-step tool orchestration. Use full workflow automation for that.

Success Case

Input:

Explain the difference between supervised and unsupervised learning

Output:

Supervised learning trains a model on labeled data to predict labels, while unsupervised learning finds patterns or structure in unlabeled data.

Boundary Case

Input:

Fix:

Provide a valid query string.

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Workflow Steps

1. Receive and validate {query}, ensuring it is non-empty and <= 500 characters.
2. Call the knowledge base search API with {query} to retrieve related documents.
3. Aggregate and summarize the retrieved results, extracting key points.
4. Format the final answer in {output_format} and return to the user.