plugins/utils/skills/parallel-dispatch/SKILL.md
Launch multiple agents concurrently, collect their results, and handle timeouts for fan-out orchestration patterns
npx skillsauth add jmagly/aiwg parallel-dispatchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Generic parallel agent orchestration utility for launching multiple agents concurrently.
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
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.jsondata-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.