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From copilot-studio
Adds SearchAndSummarizeContent or AnswerQuestionWithAI nodes to Copilot Studio topics for grounded generative answers from knowledge sources. Replaces /add-node for required patterns like ConditionGroup, autoSend, responseCaptureType.
npx claudepluginhub microsoft/skills-for-copilot-studio --plugin copilot-studioHow this skill is triggered — by the user, by Claude, or both
Slash command
/copilot-studio:add-generative-answers <topic-name or "new"><topic-name or "new">copilot-studio-authorThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Add `SearchAndSummarizeContent` nodes to generate responses grounded in the agent's knowledge sources.
Generates Copilot Studio topic YAML files for agent conversations, auto-discovering agents, matching templates, validating schema kinds, and using unique node IDs.
Generates comprehensive 500-1000 line expert agent prompts for Claude Code with detailed patterns, code examples, and best practices. Triggers on 'spawn agent', 'create agent', 'generate expert' phrases.
Searches USPTO patent and trademark records from official APIs including PatentSearch, TSDR, and assignment databases.
Share bugs, ideas, or general feedback.
Add SearchAndSummarizeContent nodes to generate responses grounded in the agent's knowledge sources.
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:
If the user just wants the agent to answer questions from its knowledge, adding the knowledge source may be enough.
Auto-discover the agent directory:
Glob: **/agent.mcs.yml
NEVER hardcode an agent name.
Determine the approach based on what the user needs:
Look up the schema for both nodes:
node ${CLAUDE_SKILL_DIR}/../../scripts/schema-lookup.bundle.js resolve CreateSearchQuery
node ${CLAUDE_SKILL_DIR}/../../scripts/schema-lookup.bundle.js resolve SearchAndSummarizeContent
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.SearchKnowledgeSources + CreateSearchQuery for raw results without AI summarization (insurance policies, HR docs, legal text).Ask the user to clarify the behavior (if not already clear from their request):
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.
Generate unique IDs for all nodes (format: <nodeType>_<6-8 random alphanumeric>).
Build the YAML using the appropriate pattern. For full YAML examples, see patterns.md. For the complete property reference table, see property-reference.md.
| Node | Use When | Data Source | Output |
|---|---|---|---|
SearchAndSummarizeContent | You want answers grounded in the agent's knowledge sources (websites, SharePoint, Dataverse) | Agent's configured knowledge | AI-summarized response |
SearchKnowledgeSources | You need verbatim/exact content — insurance policies, legal text, HR docs — where AI summarization could lose details | Agent's configured knowledge | Raw search results (no AI summary) |
AnswerQuestionWithAI | You want a response based only on conversation history and general model knowledge | No external data | AI-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.
When using knowledgeSources to restrict the search to specific sources:
/add-knowledge)knowledge/ directory.mcs.yml extensionExample: if the file is cre3c_agent.topic.MyDocs_abc123.mcs.yml, the reference is:
knowledgeSources:
kind: SearchSpecificKnowledgeSources
knowledgeSources:
- cre3c_agent.topic.MyDocs_abc123