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Allow seeding a new LearningAgent from an existing one by passing an
optional template path. Copies core-knowledge.md, topics, and learnings
from the template as a starting point, which the user can then customize.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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- **learning_from_issues.md** — Included during the `incorporate-learnings` step. Use this to guide how learnings are integrated — e.g., preferences for topics vs learnings, naming conventions, or areas of core-knowledge that should stay concise.
Copy file name to clipboardExpand all lines: learning_agents/skills/create-agent/SKILL.md
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@@ -9,34 +9,49 @@ Create a new LearningAgent and guide the user through initial configuration.
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## Arguments
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`$ARGUMENTS` is the agent name. Use dashes for multi-word names (e.g., `rails-activejob`). If not provided, ask the user what to name the agent.
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`$ARGUMENTS` contains the agent name and an optional template path, separated by whitespace.
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-**Agent name** (required): Use dashes for multi-word names (e.g., `rails-activejob`). If not provided, ask the user what to name the agent.
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-**Template agent path** (optional): Path to an existing learning agent directory (e.g., `.deepwork/learning-agents/my-existing-agent`). If provided, the new agent is seeded with the template's `core-knowledge.md`, `topics/`, and `learnings/` as a starting point. The user can then customize the copied content during configuration.
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## Procedure
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### Step 1: Validate and Run Scaffold Script
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Parse `$ARGUMENTS` to extract the agent name (first word) and optional template path (second word, if present).
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If the name contains spaces or uppercase letters, normalize to lowercase dashes (e.g., "Rails ActiveJob" → `rails-activejob`).
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Check `.claude/agents/` for an existing file matching `<agent-name>.md`. If found, inform the user of the conflict and ask how to proceed.
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If a template path was provided, verify it exists and contains `core-knowledge.md`. If not, inform the user and ask how to proceed.
If the script reports that directories already exist, inform the user and ask whether to proceed with updating the configuration or stop.
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If a template was used, inform the user what was copied (the script output will list the counts).
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### Step 2: Configure the Agent
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Ask the user about the agent's domain:
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- What domain or area of expertise does this agent cover?
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- What kinds of tasks will it be delegated to handle?
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If a template was used, read the copied `core-knowledge.md` and present it to the user. Ask if they want to keep it as-is, modify it for the new agent's focus, or replace it entirely.
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Based on their answers, update:
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1.**`.deepwork/learning-agents/<agent-name>/core-knowledge.md`**: Replace the TODO content with the agent's core expertise in second person ("You should...", "You are an expert on...").
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1.**`.deepwork/learning-agents/<agent-name>/core-knowledge.md`**: If created from scratch, replace the TODO content with the agent's core expertise in second person ("You should...", "You are an expert on..."). If seeded from a template, adapt the content to reflect the new agent's specific focus area.
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Example:
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```
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### Step 3: Seed Initial Knowledge (Optional)
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Ask the user if they want to seed any initial topics or learnings. If yes, create files using these formats:
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If a template was used and topics/learnings were copied, list what was copied and ask if the user wants to review, remove, or add to them.
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Otherwise, ask the user if they want to seed any initial topics or learnings. If yes, create files using these formats:
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