workflow-orchestrator

workflow-orchestrator is a skill for Claude Code, Codex from SHAdd0WTAka/Zen-Ai-Pentest. It costs 85 tokens per session (1,822 once invoked), scanned A, original, MIT.

A workflow manager for multi-step penetration tests, which are authorized security checks that look for weaknesses in systems. It runs reconnaissance, vulnerability scanning, and later steps in order while tracking dependencies and state.

In plain words
What is it for?
Use it to run repeated security-testing workflows, pass reconnaissance results into vulnerability scans, and manage conditional exploitation or fallback steps.
Why use it?
It coordinates modules that depend on earlier results and can retry, re-evaluate, or use a fallback when a step does not produce the expected result.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to run repeated security-testing workflows, pass reconnaissance results into vulnerability scans, and manage conditional exploitation or fallback steps.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shadd0wtaka/zen-ai-pentest/workflow-orchestrator
Install

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.

Any agent
npx skills add SHAdd0WTAka/Zen-Ai-Pentest --skill workflow-orchestrator
Clone the repo
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-Pentest

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for workflow-orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/skills/shadd0wtaka/zen-ai-pentest/workflow-orchestrator/github.svg)](https://agentmods.dev/skills/shadd0wtaka/zen-ai-pentest/workflow-orchestrator)
Your own site
<a href="https://agentmods.dev/skills/shadd0wtaka/zen-ai-pentest/workflow-orchestrator"><img src="https://agentmods.dev/badge/skills/shadd0wtaka/zen-ai-pentest/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.

agentmods 80×15 button for workflow-orchestrator

Your own site · 80×15
<a href="https://agentmods.dev/skills/shadd0wtaka/zen-ai-pentest/workflow-orchestrator"><img src="https://agentmods.dev/badge/skills/shadd0wtaka/zen-ai-pentest/workflow-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,822 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00085 $0.01822
Opus 5 $0.00043 $0.00911
Sonnet 5 $0.00017 $0.00364
Haiku 4.5 $0.00009 $0.00182

Measured 13d ago against content hash b447d372bbcb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

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 13d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/__init__.py, scripts/adaptive_strategy.py, scripts/dependency_chain.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/workflow-orchestrator/SKILL.md · 251 lines

How it starts

The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Workflow Orchestrator Skill

Manages cyclic testing workflows with dependency chaining, adaptive re-evaluation, and intelligent state management.

Quick Start

from scripts.workflow_engine import WorkflowEngine
from scripts.dependency_chain import DependencyChain
from scripts.state_manager import StateManager

# Initialize workflow
state = StateManager(target="example.com")
engine = WorkflowEngine(state)

# Define dependency chain
chain = DependencyChain()
chain.add_step("recon", NmapModule(), required=True)
chain.add_step("vuln_scan", NucleiModule(),
               depends_on=["recon"],
               input_mapper=lambda r: {"ports": r.open_ports})
chain.add_step("exploit", ExploitModule(),
               depends_on=["vuln_scan"],
               fallback=EnumModule())  # Fallback if no vulns

# Execute with iterations
results = await engine.execute(chain, max_iterations=3)

Workflow Architecture

┌─────────────────────────────────────────────────────────────┐
│                    WORKFLOW ITERATION                        │
├─────────────────────────────────────────────────────────────┤
│  1. CHECK STATE → Skip if already tested                     │
│  2. EXECUTE MODULE → Run with dependencies                   │
│  3. EVALUATE RESULTS → Success / Empty / Error               │
│  4. ADAPT STRATEGY → Fallback if empty                       │
│  5. CHAIN OUTPUTS → Feed into next modules                   │
│  6. UPDATE STATE → Mark tested, store findings               │
│  7. ITERATE → Continue until max_iterations or complete      │
└─────────────────────────────────────────────────────────────┘

Core Components

1. Dependency Chaining (scripts/dependency_chain.py)

Manages execution order and data flow between modules:

chain = DependencyChain()

# Reconnaissance phase
chain.add_step("port_scan", NmapScanner(), required=True)
chain.add_step("service_enum", ServiceEnumerator(),
               depends_on=["port_scan"])

# Vulnerability phase  
chain.add_step("web_scan", NucleiScanner(),
               depends_on=["port_scan"],
               condition=lambda ctx: 80 in ctx.get("port_scan", {}).ports or
                                    443 in ctx.get("port_scan", {}).ports)

# Exploitation phase
chain.add_step("sql_exploit", SQLMapModule(),
               depends_on=["web_scan"],
               condition=lambda ctx: "sql_injection" in ctx.findings)

Read the full file on GitHub · 251 lines

Changes

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.

  1. 13d ago First seen · 251 lines · 85 tokens per session scan A b447d372bbcb

Subscribe to this mod's changes

workflow-orchestrator is a skill published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (455 stars, last pushed yesterday), licensed MIT. It adds 85 tokens to every session and 1,822 once invoked, about $0.0004 per session on Opus 5. 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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