Generic parallel agent orchestration utility for launching multiple agents concurrently.
Launches multiple agents in parallel for concurrent analysis and review tasks.
/plugin marketplace add jmagly/aiwg/plugin install utils@aiwgThis skill inherits all available tools. When active, it can use any tool Claude has access to.
scripts/parallel_dispatcher.pyGeneric parallel agent orchestration utility for launching multiple agents concurrently.
This skill provides the foundational infrastructure for launching multiple agents in parallel, collecting their results, and handling timeouts. It is used by higher-level skills like artifact-orchestration, review-synthesis, and gate-evaluation.
When triggered, this skill:
Parses agent configuration:
Prepares agent-specific prompts:
Launches agents in parallel:
Collects results:
Returns consolidated results:
dispatch:
name: "artifact-review"
timeout: 300 # seconds
agents:
- name: security-architect
prompt: |
Review the artifact at {artifact_path} for security concerns.
Focus on: authentication, authorization, data protection, input validation.
Output format: structured findings with severity ratings.
- name: test-architect
prompt: |
Review the artifact at {artifact_path} for testability.
Focus on: test coverage gaps, edge cases, integration points.
Output format: test recommendations with priority.
- name: requirements-analyst
prompt: |
Review the artifact at {artifact_path} for requirements traceability.
Focus on: requirement coverage, gaps, conflicts.
Output format: traceability assessment.
context:
artifact_path: ".aiwg/architecture/sad.md"
requirements_path: ".aiwg/requirements/"
result_format: structured # or 'raw'
aggregate: true # combine findings
User: "Launch parallel review of the SAD by security-architect, test-architect, and requirements-analyst"
Skill executes:
1. Loads SAD from .aiwg/architecture/
2. Prepares review prompts for each agent
3. Dispatches all three agents in single message
4. Collects reviews (timeout: 5 min)
5. Returns structured results
User: "Dispatch agents with config from .aiwg/config/review-config.yaml"
Skill executes:
1. Loads configuration file
2. Validates agent names exist
3. Prepares prompts from templates
4. Dispatches with configured timeout
5. Returns results in configured format
{
"dispatch_id": "review-20251208-143022",
"status": "completed",
"duration_seconds": 127,
"agents": {
"security-architect": {
"status": "success",
"duration": 45,
"output": {
"findings": [...],
"severity_summary": {...},
"recommendations": [...]
}
},
"test-architect": {
"status": "success",
"duration": 52,
"output": {
"coverage_gaps": [...],
"test_recommendations": [...],
"priority_order": [...]
}
},
"requirements-analyst": {
"status": "success",
"duration": 38,
"output": {
"traced_requirements": [...],
"gaps": [...],
"conflicts": [...]
}
}
},
"aggregate": {
"total_findings": 12,
"critical_issues": 2,
"recommendations": 8
}
}
{
"dispatch_id": "review-20251208-143022",
"agents": {
"security-architect": "Full text output from agent...",
"test-architect": "Full text output from agent...",
"requirements-analyst": "Full text output from agent..."
}
}
timeout_behavior:
action: "partial" # or "fail"
# partial: return results from completed agents
# fail: return error if any agent times out
failure_behavior:
action: "continue" # or "abort"
# continue: proceed with other agents
# abort: stop all if one fails
retry: 1 # retry failed agents once
For convenience, common agent combinations are pre-defined:
group: architecture-review
agents:
- security-architect
- test-architect
- requirements-analyst
- technical-writer
group: security-review
agents:
- security-architect
- security-auditor
- privacy-officer
group: documentation-review
agents:
- technical-writer
- requirements-analyst
- domain-expert
group: marketing-review
agents:
- brand-guardian
- legal-reviewer
- quality-controller
- accessibility-checker
This skill is the foundation for:
artifact-orchestration (SDLC)gate-evaluation (SDLC)review-synthesis (MMK)brand-compliance (MMK)# Using Python script
python parallel_dispatcher.py --config review-config.yaml
# With inline agents
python parallel_dispatcher.py \
--agents "security-architect,test-architect" \
--artifact ".aiwg/architecture/sad.md" \
--timeout 300
# List available groups
python parallel_dispatcher.py --list-groups
# Validate configuration
python parallel_dispatcher.py --config review-config.yaml --validate
agents/ directoriesschemas/dispatch-config.schema.jsonschemas/dispatch-result.schema.jsonSearch, retrieve, and install Agent Skills from the prompts.chat registry using MCP tools. Use when the user asks to find skills, browse skill catalogs, install a skill for Claude, or extend Claude's capabilities with reusable AI agent components.
Activates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.
Expert guidance for Next.js Cache Components and Partial Prerendering (PPR). **PROACTIVE ACTIVATION**: Use this skill automatically when working in Next.js projects that have `cacheComponents: true` in their next.config.ts/next.config.js. When this config is detected, proactively apply Cache Components patterns and best practices to all React Server Component implementations. **DETECTION**: At the start of a session in a Next.js project, check for `cacheComponents: true` in next.config. If enabled, this skill's patterns should guide all component authoring, data fetching, and caching decisions. **USE CASES**: Implementing 'use cache' directive, configuring cache lifetimes with cacheLife(), tagging cached data with cacheTag(), invalidating caches with updateTag()/revalidateTag(), optimizing static vs dynamic content boundaries, debugging cache issues, and reviewing Cache Component implementations.