Skill Workflow Orchestrator

Multi-skill workflow orchestrator. Chain multiple skills into automated pipelines, triggering entire sequences like "search → summarize → generate report → s...

Security Scan

The skill's description matches its instructions (it chains other skills), but because it can load and execute arbitrary sub-skills (including ones that perform sensitive actions) and its source is unknown, there is a meaningful risk that it could be used to trigger privileged operations without adequate safeguards.

Purpose & Capability

The name and description (workflow/orchestration) align with the SKILL.md: it parses user intent, composes a sequence of sub-skills, supports branching/retries, and passes outputs between steps. It does not request unrelated binaries, env vars, or installs, which is coherent for an orchestrator.

Instruction Scope

The SKILL.md itself does not instruct the agent to read local files or exfiltrate secrets, but it grants broad runtime authority to load and execute arbitrary sub-skills and to pass their outputs along. That means sensitive actions (sending email, accessing files, calling external APIs) are possible via downstream skills. The doc mentions user confirmation for sensitive operations but does not specify how confirmation is enforced, logged, or required by the platform.

Install Mechanism

Instruction-only skill with no install spec and no code files. This is low-risk from an installation-execution standpoint because nothing is written to disk by the skill definition itself.

Credentials

The skill declares no required environment variables or credentials. However, it can invoke other skills that may require secrets or credentials; those are not declared here, which is expected but means credential access will come from the invoked sub-skills rather than this orchestrator.

Persistence & Privilege

always:false (good). Autonomous invocation is allowed (disable-model-invocation:false), which is platform-default and reasonable for an orchestrator. That capability combined with the ability to call arbitrary sub-skills increases blast radius—especially for actions that can be performed without explicit, enforced user confirmation.

What to consider before installing

This skill is internally coherent — it does what it claims: chain and orchestrate other skills. The main risk is not in the skill itself but in what it can trigger: any sub-skill it loads may send emails, access files, or use API keys. Before installing, consider: 1) Source provenance: the skill's source is unknown and there's no homepage — prefer skills with a known publisher or code review. 2) Permission model: confirm whether the platform enforces explicit user confirmation for sensitive actions (sending messages, accessing files, making payments) and whether you can require confirmations by default. 3) Sub-skill allowlist: restrict which sub-skills this orchestrator is permitted to call (avoid allowing it to call high-privilege skills). 4) Auditing: ensure invocation logs/audit trails are available so you can review what chains ran and what data was transmitted. 5) Test safely: try with non-sensitive, read-only workflows first. If you need higher assurance, request the skill's source or an explicit security policy from the publisher.

Overview

This skill orchestrates multiple sub-skills into automated pipelines. A complete skill chain can be triggered through natural language descriptions, supporting sequential execution, conditional branching, and error handling.

Use Cases

Automatically triggers when user descriptions involve multi-step tasks, for example:

• "Search for the latest AI news, generate a summary report, and then email it to me."
• "Check the stock price; if it rises more than 5%, remind me."
• "Read the PDF file, extract the content, summarize it, and save it to notes."

Workflow Definition

1. Parse User Intent

Parse the user's natural language description into a structured skill chain:

User: "Search AI news → Summarize → Send email"
→ Parsed into:
[
  {"skill": "multi-search-engine", "task": "Search latest AI news"},
  {"skill": "content-summarizer", "task": "Generate summary"},
  {"skill": "email-skill", "task": "Send email"}
]

2. Sequential Execution

Invoke each skill in order, with the output of the previous skill serving as the input for the next:

# Pseudocode example
results = []
for step in workflow:
    skill = load_skill(step.skill)
    input_data = results[-1] if results else None
    result = skill.execute(step.task, input_data)
    results.append(result)

3. Conditional Branching

Supports if/else logic:

If [condition] → Execute [Skill A]
Else → Execute [Skill B]

Supported comparison operators:

• Numeric comparison: >, <, >=, <=, ==, !=
• String containment: contains, startswith, endswith
• Boolean checks: is_true, is_false, exists

4. Error Handling

• Retry Mechanism: Automatically retry failed steps up to 2 times
• Skip and Continue: Optionally continue executing subsequent steps when a step fails
• Fallback Execution: Support defining an alternative skill chain on failure

Built-in Templates

Template 1: Information Gathering Chain

Search → Content Extraction → Organize and Save

Use Cases: Competitor research, news tracking, data collection

Template 2: Analysis Report Chain

Fetch Data → Analyze and Process → Generate Report → Send Notification

Use Cases: Stock analysis, operational reports, data dashboards

Template 3: Content Creation Chain

Topic Selection → Search Material → Create Content → Review and Publish

Use Cases: Blog posts, social media management

Configuration Options

Specifiable within a workflow:

Option	Description	Example
timeout	Timeout per skill (seconds)	30
retry	Number of retry attempts on failure	2
continue_on_error	Whether to continue after failure	true/false
output_format	Final output format	json/markdown/text

Usage Examples

Example 1: Simple Chain

User: Search for the latest developments in quantum computing, generate a summary, and save it to notes.

{
  "steps": [
    {"skill": "multi-search-engine", "task": "Latest developments in quantum computing"},
    {"skill": "content-summarizer", "task": "Generate summary"},
    {"skill": "ima-skill", "task": "Save to notes"}
  ]
}

Example 2: With Conditional Branching

User: Check the price of BTC; if it drops below $50,000, remind me to sell.

{
  "steps": [
    {"skill": "neodata-financial-search", "task": "BTC price"},
    {
      "condition": "price < 50000",
      "then": [{"skill": "message", "task": "Remind to sell"}],
      "else": []
    }
  ]
}

Example 3: With Error Handling

User: Read this PDF, extract the table data; if it fails, send me an email notification.

{
  "steps": [
    {"skill": "pdf", "task": "Read PDF", "retry": 3},
    {"skill": "xlsx", "task": "Extract table data"}
  ],
  "on_error": {
    "skill": "email-skill",
    "task": "Send error notification"
  }
}

Notes

1. Total skill chain length is recommended not to exceed 10 steps
2. Complex workflows should be split into multiple simpler chains
3. Sensitive operations (e.g., sending emails, messages) require user confirmation
4. Periodically check the validity and latest versions of all sub-skills