plugins/agent-scaffolders/skills/create-sub-agent/SKILL.md
Design and scaffold a Claude Code sub-agent
npx skillsauth add richfrem/agent-plugins-skills create-sub-agentInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Follow the create-sub-agent skill workflow to design and generate a Claude Code agent file.
$ARGUMENTS — optional agent name or brief use-case description passed as initial context
to the design interview. Omit to start with open discovery.$ARGUMENTS is provided, use it as the starting context for agent name / purpose.md filevalidate_agent.py.github/agents/ or .claude/agents/ and ensure the path is tracked in .gitignore.Agent .md file with complete YAML frontmatter (name, description with <example> blocks,
model, maxTokens, color, permissions.allowedTools, permissions.deny) and a second-person
system prompt targeting 500-3,000 characters.
Plugin agents: flat .md file — plugins/<plugin-name>/agents/<agent-name>.md
skills/<name>/SKILL.md subdirectory format, but agents do NOT.feature-dev, code-simplifier, hookify).Local/project agents: .claude/agents/<agent-name>.md (also flat, no subdirectory).
To make an agent visible to GitHub Copilot or Claude Code for this repository, follow the Discovery-First Publication pattern:
.github/agents/ (Copilot) or .claude/agents/ (Claude)..gitignore allows the specific agent file or subdirectory.See Agent Discovery and Publication Pattern for details.
$ARGUMENTS is empty: conduct the full Phase 1 design interview — do not pre-filltools
Ingests repository files into the ChromaDB vector store. Builds or updates the vector index from a manifest or directory scan using ingest.py. Use when new files need to be indexed or the vector store is out of date. <example> user: "Index these new plugin files into the vector database" assistant: "I'll use vector-db-ingest to add them to the vector store." </example> <example> user: "The vector store is missing recent files -- update it" assistant: "I'll use vector-db-ingest to re-index the changes." </example>
data-ai
Removes stale and orphaned chunks from the ChromaDB vector store for files that have been deleted or renamed. Use after files are removed or moved to keep the vector index in sync with the filesystem. <example> user: "Clean up the vector store after I deleted some files" assistant: "I'll use vector-db-cleanup to remove orphaned chunks." </example> <example> user: "The vector database has chunks for files that no longer exist" assistant: "I'll run vector-db-cleanup to prune them." </example>
testing
Audit Vector DB coverage -- compares the live filesystem manifest against the ChromaDB index to identify coverage gaps.
development
3-Phase Knowledge Search strategy for the RLM Factory ecosystem. Auto-invoked when tasks involve finding code, documentation, or architecture context in the repository. Enforces the optimal search order: RLM Summary Scan (O(1)) -> Vector DB Semantic Search -> Grep/Exact Match. Never skip phases.