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Add Generative Answers

Organization
microsoft
add-generative-answers

Add generative answer nodes (SearchAndSummarizeContent or AnswerQuestionWithAI) to a Copilot Studio topic. Use this instead of /add-node when the user asks to add grounded answers, knowledge search, generative answers, or AI-powered responses — these nodes require specific patterns (ConditionGroup follow-up, knowledge source references, autoSend, responseCaptureType) that /add-node does not cover.

Overview

Publishermicrosoft
Repositoryskills-for-copilot-studio
Skill nameadd-generative-answers
Stars
478
Forks
101
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Add Generative Answers AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/microsoft/skills-for-copilot-studio/tree/main/skills/add-generative-answers
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/skills-for-copilot-studio.git /tmp/skills-for-copilot-studio
mkdir -p .claude/skills
cp -r /tmp/skills-for-copilot-studio/skills/add-generative-answers .claude/skills/add-generative-answers
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Add Generative Answers in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Add Generative Answers on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Add Generative Answers is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Add Generative Answers

Add SearchAndSummarizeContent nodes to generate responses grounded in the agent's knowledge sources.

Important: Do You Even Need a Topic?

When knowledge sources are added to the agent (via /add-knowledge), the AI can directly search them without any topic if it recognizes a QnA-style query. A dedicated topic with SearchAndSummarizeContent is useful when:

  • You want to restrict the search to a subset of knowledge sources (not all of them)
  • You want to control the flow around the answer (e.g., follow-up questions, formatting, adaptive cards)
  • You want to process the response before showing it (e.g., extract content, combine with other data)
  • You want to use a specific input other than the user's last message

If the user just wants the agent to answer questions from its knowledge, adding the knowledge source may be enough.

Instructions

  1. Auto-discover the agent directory:

    Glob: **/agent.mcs.yml

    NEVER hardcode an agent name.

  2. Determine the approach based on what the user needs:

    • Add to existing topic: Read the target topic and insert a SearchAndSummarizeContent node
    • Create new search topic: Generate a complete topic with the search pattern
  3. Look up the schema for both nodes:

    bash
    node ${CLAUDE_SKILL_DIR}/../../scripts/schema-lookup.bundle.js resolve CreateSearchQuery
    node ${CLAUDE_SKILL_DIR}/../../scripts/schema-lookup.bundle.js resolve SearchAndSummarizeContent
  4. Read settings.mcs.yml to check if GenerativeActionsEnabled: true. This determines the best pattern:

    • GenerativeActionsEnabled: true → prefer Pattern 2 (Orchestrator): use topic inputs/outputs and let the orchestrator handle the response. This is the best approach for generative-orchestrated agents.
    • GenerativeActionsEnabled: false (or not set) → use Pattern 1 (Direct Response): autoSend: false + manual SendActivity, or Pattern 3 (Fallback Search) for a simple all-knowledge fallback.
    • Verbatim/exact content needed → use Pattern 4 (Precision Search): SearchKnowledgeSources + CreateSearchQuery for raw results without AI summarization (insurance policies, HR docs, legal text).
  5. Ask the user to clarify the behavior (if not already clear from their request):

    • Should it search all knowledge sources or only specific ones?
    • Should general model knowledge also be used, or only the configured knowledge sources?
    • Should the response be sent automatically to chat, or processed first (e.g., custom formatting, adaptive card, combined with other data)?
  6. Always precede SearchAndSummarizeContent with CreateSearchQuery to preserve conversational context. Never pass =System.Activity.Text directly to SearchAndSummarizeContent — the raw last message may lack context (e.g., "tell me more about that"). CreateSearchQuery rewrites the input into an optimized search query. Access the result via Topic.<ResultVar>.SearchQuery.

  7. Generate unique IDs for all nodes (format: <nodeType>_<6-8 random alphanumeric>).

  8. Build the YAML using the appropriate pattern. For full YAML examples, see patterns.md. For the complete property reference table, see property-reference.md.

SearchAndSummarizeContent vs AnswerQuestionWithAI

NodeUse WhenData SourceOutput
SearchAndSummarizeContentYou want answers grounded in the agent's knowledge sources (websites, SharePoint, Dataverse)Agent's configured knowledgeAI-summarized response
SearchKnowledgeSourcesYou need verbatim/exact content — insurance policies, legal text, HR docs — where AI summarization could lose detailsAgent's configured knowledgeRaw search results (no AI summary)
AnswerQuestionWithAIYou want a response based only on conversation history and general model knowledgeNo external dataAI-generated response

Use SearchAndSummarizeContent for the vast majority of cases (what people call "generative answers"). Use SearchKnowledgeSources when you need raw, unsummarized results for precision scenarios (pair with CreateSearchQuery for better search accuracy). Use AnswerQuestionWithAI only when you explicitly want the model to respond without consulting knowledge sources.

Knowledge Source References

When using knowledgeSources to restrict the search to specific sources:

  1. The knowledge source must already exist in the agent (add it first with /add-knowledge)
  2. Find the knowledge source filename in the agent's knowledge/ directory
  3. Reference it without the .mcs.yml extension

Example: if the file is cre3c_agent.topic.MyDocs_abc123.mcs.yml, the reference is:

yaml
knowledgeSources:
  kind: SearchSpecificKnowledgeSources
  knowledgeSources:
    - cre3c_agent.topic.MyDocs_abc123

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Add Generative Answers AI skill do?

Add generative answer nodes (SearchAndSummarizeContent or AnswerQuestionWithAI) to a Copilot Studio topic. Use this instead of /add-node when the user asks to add grounded answers, knowledge search, generative answers, or AI-powered responses — these nodes require specific patterns (ConditionGroup follow-up, knowledge source references, autoSend, responseCaptureType) that /add-node does not cover.

Why use Add Generative Answers on TypingMind?

Because you install it once and use it with any model. Add Generative Answers is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Add Generative Answers in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/skills-for-copilot-studio/tree/main/skills/add-generative-answers. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Add Generative Answers?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Add Generative Answers?

As many as you like. As long as a model supports skills, you can use Add Generative Answers with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Add Generative Answers AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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