# Skills For Copilot Studio > 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. Use when this capability is needed. - Skill: `tomevault-io/skills-for-copilot-studio` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/skills-for-copilot-studio` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/skills-for-copilot-studio/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/skills-for-copilot-studio --- # 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..SearchQuery`. 7. **Generate unique IDs** for all nodes (format: `_<6-8 random alphanumeric>`). 8. **Build the YAML** using the appropriate pattern. For full YAML examples, see [patterns.md](patterns.md). For the complete property reference table, see [property-reference.md](property-reference.md). ## SearchAndSummarizeContent vs AnswerQuestionWithAI | 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. ## 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 ``` --- > Source: [microsoft/skills-for-copilot-studio](https://github.com/microsoft/skills-for-copilot-studio) — distributed by [TomeVault](https://tomevault.io).