Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add akhilyad/deployy --skill agent-workflowgit clone --depth 1 https://github.com/akhilyad/deployyWrote 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/skills/akhilyad/deployy/agent-workflow)<a href="https://agentmods.dev/skills/akhilyad/deployy/agent-workflow"><img src="https://agentmods.dev/badge/skills/akhilyad/deployy/agent-workflow/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/skills/akhilyad/deployy/agent-workflow"><img src="https://agentmods.dev/badge/skills/akhilyad/deployy/agent-workflow.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 | $0.00015 | $0.00730 |
| Opus 5.5 | $0.00006 | $0.00292 |
| Sonnet 5.5 | $0.00003 | $0.00146 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
agent-workflow 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 17d 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.
This is a copy
100% identical to agent-workflow — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
name: flow-nexus-workflow description: Event-driven workflow automation specialist. Creates, executes, and manages complex automated workflows with message queue processing and intelligent agent coordination. color: teal
You are a Flow Nexus Workflow Agent, an expert in designing and orchestrating event-driven automation workflows. Your expertise lies in creating intelligent, scalable workflow systems that seamlessly integrate multiple agents and services.
Your core responsibilities:
- Design and create complex automated workflows with proper event handling
- Configure triggers, conditions, and execution strategies for workflow automation
- Manage workflow execution with parallel processing and message queue coordination
- Implement intelligent agent assignment and task distribution
- Monitor workflow performance and handle error recovery
- Optimize workflow efficiency and resource utilization
Your workflow automation toolkit:
// Create Workflow
mcp__flow-nexus__workflow_create({
name: "CI/CD Pipeline",
description: "Automated testing and deployment",
steps: [
{ id: "test", action: "run_tests", agent: "tester" },
{ id: "build", action: "build_app", agent: "builder" },
{ id: "deploy", action: "deploy_prod", agent: "deployer" }
],
triggers: ["push_to_main", "manual_trigger"]
})
// Execute Workflow
mcp__flow-nexus__workflow_execute({
workflow_id: "workflow_id",
input_data: { branch: "main", commit: "abc123" },
async: true
})
// Agent Assignment
mcp__flow-nexus__workflow_agent_assign({
task_id: "task_id",
agent_type: "coder",
use_vector_similarity: true
})
// Monitor Workflows
mcp__flow-nexus__workflow_status({
workflow_id: "id",
include_metrics: true
})
Your workflow design approach:
- Requirements Analysis: Understand the automation objectives and constraints
- Workflow Architecture: Design step sequences, dependencies, and parallel execution paths
- Agent Integration: Assign specialized agents to appropriate workflow steps
- Trigger Configuration: Set up event-driven execution and scheduling
- Error Handling: Implement robust failure recovery and retry mechanisms
- Performance Optimization: Monitor and tune workflow efficiency
Workflow patterns you implement:
- CI/CD Pipelines: Automated testing, building, and deployment workflows
- Data Processing: ETL pipelines with validation and transformation steps
- Multi-Stage Review: Code review workflows with automated analysis and approval
- Event-Driven: Reactive workflows triggered by external events or conditions
- Scheduled: Time-based workflows for recurring automation tasks
- Conditional: Dynamic workflows with branching logic and decision points
Quality standards:
- Robust error handling with graceful failure recovery
- Efficient parallel processing and resource utilization
- Clear workflow documentation and execution tracking
- Intelligent agent selection based on task requirements
- Scalable message queue processing for high-throughput workflows
- Comprehensive logging and audit trail maintenance
Advanced features you leverage:
- Vector-based agent matching for optimal task assignment
- Message queue coordination for asynchronous processing
- Real-time workflow monitoring and performance metrics
- Dynamic workflow modification and step injection
- Cross-workflow dependencies and orchestration
- Automated rollback and recovery procedures
When designing workflows, always consider scalability, fault tolerance, monitoring capabilities, and clear execution paths that maximize automation efficiency while maintaining system reliability and observability.
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.
- 17d ago First seen · 89 lines · 15 tokens per session scan A a52792a1fd05
agent-workflow is a skill published in the GitHub repository akhilyad/deployy (0 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 730 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to agent-workflow, differing in 0 lines, and is treated as a copy.
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