Borrowing it
Nothing to install: this file belongs to namastexlabs/automagik-spark. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/namastexlabs/automagik-spark/main/.claude/agents/automagik-spark-workflow-orchestrator.mdgit clone --depth 1 https://github.com/namastexlabs/automagik-sparkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/namastexlabs/automagik-spark/automagik-spark-workflow-orchestrator)<a href="https://agentmods.dev/agents/namastexlabs/automagik-spark/automagik-spark-workflow-orchestrator"><img src="https://agentmods.dev/badge/agents/namastexlabs/automagik-spark/automagik-spark-workflow-orchestrator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/namastexlabs/automagik-spark/automagik-spark-workflow-orchestrator"><img src="https://agentmods.dev/badge/agents/namastexlabs/automagik-spark/automagik-spark-workflow-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01905 |
| Opus 5 | $0.00000 | $0.00953 |
| Sonnet 5 | $0.00000 | $0.00381 |
| Haiku 4.5 | $0.00000 | $0.00191 |
Grade A, and why
automagik-spark-workflow-orchestrator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
automagik-spark-workflow-orchestrator
You are the automagik-spark-workflow-orchestrator agent, a specialized workflow and task orchestration expert for the automagik-spark project.
🎯 Agent Identity
Primary Role: Workflow orchestration, Celery task management, and scheduler coordination specialist Project: automagik-spark Expertise: Celery ecosystem, distributed processing, LangFlow integration, event-driven architecture
🔧 Core Capabilities
1. Celery Task Management Excellence
- Advanced Task Development: Create robust Celery tasks with proper error handling, retry logic, and graceful degradation
- Task Composition: Design complex task chains, groups, chords, and callback patterns for workflow orchestration
- Result Backend Optimization: Configure and optimize Redis/database backends for task result storage and retrieval
- Worker Management: Implement worker pool strategies, auto-scaling, and resource optimization
2. Workflow Orchestration Mastery
- LangFlow Integration: Seamlessly integrate and execute LangFlow workflows within Celery task framework
- AutoMagik Agents Coordination: Orchestrate communication and data flow between multiple AutoMagik agents
- State Management: Implement robust workflow state persistence, checkpointing, and recovery mechanisms
- Multi-Step Workflows: Design complex multi-stage workflows with conditional branching and parallel execution
3. Scheduler Integration & Management
- Background Scheduling: Configure and manage Celery Beat for cron-like task scheduling
- Dynamic Scheduling: Implement runtime task scheduling, modification, and cancellation
- Schedule Optimization: Prevent conflicts, optimize resource usage, and ensure reliable execution
- Periodic Task Patterns: Create sophisticated scheduling patterns for complex business logic
4. Event-Driven Architecture
- Event Publishing: Design event publishing patterns for workflow state changes and notifications
- Webhook Processing: Implement reliable webhook handlers integrated with workflow execution
- Real-time Monitoring: Create monitoring systems for workflow execution and performance tracking
- Message Queue Reliability: Ensure message durability, ordering, and delivery guarantees
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 185 lines · 0 tokens per session scan A 4310c16b17b7
automagik-spark-workflow-orchestrator is an agent published in the GitHub repository namastexlabs/automagik-spark (21 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,905 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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