Agent manager
Create, validate, version, and list AIDA-managed Claude Code subagent definition files (two-phase API). Use for CRUD on agent .md definitions, routed through /aida extension management. Do NOT use to run, dispatch, or consult a subagent — this only authors and maintains the definition files.From its SKILL.md
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SKILL.md
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Agent Manager
Focused management interface for Claude Code agent (subagent)
definitions. Handles the full lifecycle of agent .md files
and their knowledge/ directories.
Activation
This skill activates when:
- User invokes
/aida agent [create|validate|version|list] - Agent management is needed
Operations
Command Routing
Parse the command to determine:
- Operation:
create,validate,version,list - Arguments: name, description, options
The component type is always agent -- no type selection
is needed.
Create Operations
For create operations, use the three-phase orchestration
pattern:
Phase 1: Gather Context (Python)
Run the script to infer metadata and get questions:
python {base_directory}/scripts/manage.py \
--get-questions \
--context='{"operation": "create", "description": "user description", "location": "user"}'
Returns:
{
"inferred": {
"name": "inferred-name",
"version": "0.1.0",
"tags": ["custom"],
"base_path": "~/.claude/agents/inferred-name"
},
"questions": [],
"project_context": {
"languages": ["python"],
"frameworks": ["fastapi"]
}
}
Phase 2: Generate Content (Agent)
Spawn the claude-code-expert agent with complete context
and output contract:
Operation: CREATE
Type: agent
Requirements:
- Name: {inferred.name}
- Description: {user_description}
- Location: {inferred.base_path}
- Project Context: {project_context}
- User Answers: {answers to questions}
Output Format:
Return a JSON object with this exact structure:
{
"validation": {
"passed": true|false,
"issues": [
{
"severity": "error|warning",
"message": "description",
"suggestion": "how to fix"
}
]
},
"files": [
{
"path": "agents/{name}/{name}.md",
"content": "..."
},
{
"path": "agents/{name}/knowledge/index.md",
"content": "..."
}
],
"summary": {
"created": ["list of relative paths"],
"next_steps": ["actionable items for user"]
}
}
Handle agent response:
- Parse the JSON response
- If
validation.passedis false with errors:- Report issues to user
- Ask if they want to proceed or provide more info
- If validation passed (or user chose to proceed):
- Continue to Phase 3
Phase 3: Write Files (Python)
Pass agent output to Python for file creation:
python {base_directory}/scripts/manage.py \
--execute \
--context='{"operation": "create", "agent_output": <agent_json>}'
The script:
- Validates file structure (required fields, frontmatter)
- Creates directories (including
knowledge/) - Writes files
- Returns success/failure
Validate Operations
For validate operations:
- Run validation script
- Report results with any errors
Script invocation:
# Validate specific agent
python {base_directory}/scripts/manage.py --execute \
--context='{"operation": "validate", "name": "my-agent"}'
# Validate all agents
python {base_directory}/scripts/manage.py --execute \
--context='{"operation": "validate", "all": true, "location": "all"}'
Version Operations
For version operations:
- Find the agent
- Bump version (major, minor, or patch)
- Update the file
- Report the version change
Script invocation:
python {base_directory}/scripts/manage.py --execute \
--context='{"operation": "version", "name": "my-agent", "bump": "patch"}'
List Operations
For list operations:
- Search specified locations
- Parse agent metadata from frontmatter
- Return formatted list
Script invocation:
python {base_directory}/scripts/manage.py --execute \
--context='{"operation": "list", "location": "all", "format": "table"}'
Path Resolution
Base Directory: Provided when skill loads via
<command-message> tags.
Script Execution:
{base_directory}/scripts/manage.py
Reference Files:
{base_directory}/references/create-workflow.md
{base_directory}/references/validate-workflow.md
{base_directory}/references/schemas.md
Location Options
| Location | Path | Use Case |
|---|---|---|
user | ~/.claude/ | Personal agents |
project | ./.claude/ | Project-specific agents |
plugin | Custom path | Plugin development |
Example Workflow
Creating an Agent (Full Flow)
User: /aida agent create "handles database migrations"
1. Parse: operation=create, description="handles database migrations"
2. Phase 1 (Python):
python manage.py --get-questions --context='{...}'
Returns:
- inferred: name="database-migration", version="0.1.0"
- questions: [location question]
- project_context: {languages: ["python"]}
3. Ask user questions (if any):
"Where should we create this agent?"
4. Phase 2 (Agent):
Spawn claude-code-expert with context + output contract
Agent returns JSON with files array
5. Phase 3 (Python):
python manage.py --execute --context='{"operation": "create", "agent_output": {...}}'
- Validates structure
- Creates directories + knowledge/
- Writes files
6. Report to user:
"Created agent 'database-migration' with 3 files"
Resources
scripts/
- manage.py - Entry point for two-phase API
- operations/ - Operation modules
- utils.py - Shared utilities (re-export shim)
- extensions.py - Agent operations
references/
- create-workflow.md - Agent creation workflow
- validate-workflow.md - Agent validation rules
- schemas.md - Agent frontmatter schema