Add and configure agents

Adding an agent Three ways. Pick whichever feels fastest in the moment. 1. Drag from the Agent Palette Open the palette from the left edge of the canvas (the icon strip). Drag any role card onto the canvas. Release where you want the agent. Cerevisor places it in the nearest column. 2. Right-click the canvas Right-click any empty area. Choose Add Agent → [Role] . The agent appears at your cursor position. 3. Press 1–9 or 0 Pressing a number key enters placement mode for the N-th role in your palette order. Your cursor becomes a ghost of the agent. Click anywhere to place. Press Escape (or right-click) to cancel. This is the fastest path once you know your palette order. Reorder roles in Settings → Agents to put your favorites at 1 and 2. 4. Drag a Custom Agent template If you've saved a custom agent template (see Reference → Agent roles → Custom Agent ), drag the template card from the palette onto the canvas. It carries its saved skills, model, and instructions. Configuring an agent Click the agent's name or role badge to open the Agent Config popup. Every field below is in that popup, top to bottom. Name The agent's display name on its card. Plain text. Choose something specific, "Senior researcher" beats "Researcher 2" for any workflow with more than one agent of the same role. Role (read-only) The role badge. You set this when you added the agent; to change it, delete the agent and add a new one with the role you want. (We don't allow in-place role swaps because the role drives smart defaults that you may have customized.) Role description A textarea. Free-form text describing what kind of agent this is. The default is the role's stock description; edit it to add specifics. Example: A researcher specialized in EU funding programs (Horizon Europe, EIC, Eurostars). Knows the eligibility quirks and reporting requirements. Cross-checks call deadlines on the official Funding & Tenders portal. Goes into the agent's system prompt. Instructions A textarea. The most important field. This is where you tell the agent what to do in this specific workflow . Good instructions: Are concrete about the goal. Specify the input the agent will receive (from upstream agents or workflow input). Specify the output the agent should produce. Mention any constraints (length, format, sources). Mention any tools the agent should prefer (e.g. "use the recency-research skill"). Bad instructions: "Do research." (Too vague: the agent will produce generic output.) Output definition A prose textarea, plus optional structured fields. The prose describes what the output should look like in natural language: A 600-word markdown blog post with a title, a one-sentence summary line at the top, and 3-4 H2 sections. Tone: matter-of-fact, second-person, no hype. Include inline source citations. Optional structured fields : Required headings : chip picker. Agent's output must include these H2 sections. Min words : integer. Agent's output must hit this length. Deliverables : chip pi

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