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glm5-parallel
Model-agnostic parallel execution with Agent Teams coordination
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Model-agnostic parallel execution with Agent Teams coordination
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Full orchestration workflow with swarm mode: evaluate -> clarify -> classify -> persist -> plan mode -> spawn teammates -> execute -> validate -> retrospective. Use when: (1) implementing features, (2) complex refactoring, (3) multi-file changes, (4) tasks requiring coordination. Triggers: /orchestrator, /orch, 'orchestrate', 'full workflow', 'implement feature'.
Comprehensive research skill using Zai MCP web search and native Claude Code tools
Smart Forking - Find and fork from relevant historical sessions using parallel memory search across vault, handoffs, and ledgers
Apply adversarial opposite-analysis to plans, specs, architecture, code changes, and claims. Use when the user asks for adversarial review, opposing analysis, contrarian review, red-team reasoning, or Z.ai and MiniMax cross-checks through the Ralph MCP router.
Test case mutation and variation generator for adversarial testing
Patterns for using Context7 MCP for library documentation (v2.25)
| name | glm5-parallel |
| description | Model-agnostic parallel execution with Agent Teams coordination |
| allowed-tools | ["Bash","Read","Write","Task","TaskCreate","TaskList","TaskGet","TaskUpdate","TeamCreate","SendMessage"] |
Model-agnostic parallel execution with Agent Teams coordination for comprehensive task execution.
Note: Despite the name, this skill is model-agnostic as of v2.88.0. It works with any model configured in Agent Teams.
/glm5-parallel <task> [--roles coder,reviewer,tester]
/glm5-parallel "Implement OAuth2 authentication" --roles coder,reviewer,tester
This spawns 3 teammates:
# Generate task ID
TASK_ID="parallel-$(date +%s)"
# Parse roles
ROLES="coder,reviewer,tester"
# Spawn in parallel
for ROLE in $(echo $ROLES | tr ',' ' '); do
.claude/scripts/glm5-teammate.sh "$ROLE" "<task>" "${TASK_ID}-${ROLE}" &
done
# Wait for all
wait
# Aggregate results
for ROLE in $(echo $ROLES | tr ',' ' '); do
echo "=== $ROLE ==="
cat .ralph/teammates/${TASK_ID}-${ROLE}/status.json | jq '.output_summary'
done
If no --roles specified:
coder - Implementationreviewer - Code reviewtester - Test generationCreates parallel status files:
.ralph/teammates/{task_id}-coder/status.json.ralph/teammates/{task_id}-reviewer/status.json.ralph/teammates/{task_id}-tester/status.jsonAggregated in .ralph/team-status.json
Optimal Scenario: Pure Agent Teams (Native)
This skill uses Pure Agent Teams with native coordination - no custom subagent specialization needed.
TeamCreate
→ Task(prompt, subagent_type) for each parallel workstream
→ Native agents execute in parallel
→ Aggregate results
→ Complete
// Create team for coordination
TeamCreate(team_name="parallel-{timestamp}", description="Parallel execution for: {task}")
// Spawn native agents in parallel
const workstreams = [
{ task: "Implement feature X", files: ["src/a.ts"] },
{ task: "Implement feature Y", files: ["src/b.ts"] },
{ task: "Write tests", files: ["tests/*.test.ts"] }
];
workstreams.forEach(work => {
Task(
subagent_type="coder", // Native agent type
team_name="parallel-{timestamp}",
input=work
);
});
Esta skill genera reportes automáticos completos para trazabilidad:
Cuando esta skill completa, se genera automáticamente:
docs/actions/glm5-parallel/{timestamp}.md.claude/metadata/actions/glm5-parallel/{timestamp}.jsonCada reporte incluye:
# Listar todos los reportes de esta skill
ls -lt docs/actions/glm5-parallel/
# Ver el reporte más reciente
cat $(ls -t docs/actions/glm5-parallel/*.md | head -1)
# Buscar reportes fallidos
grep -l "Status: FAILED" docs/actions/glm5-parallel/*.md
source .claude/lib/action-report-lib.sh
start_action_report "glm5-parallel" "Task description"
# ... ejecución ...
complete_action_report "success" "Summary" "Recommendations"