| Name | skeptofox JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | None |
| Summary | A machine-human intelligence framework for declarative programming, Agentic AI and automation workflows |
| upload_time | 2025-07-31 13:27:21 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License
Copyright (c) 2025 skeptofox
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE. |
| keywords |
agentic ai
automation
declarative programming
human-in-the-loop
machine intelligence
workflow
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# skeptofox
skeptofox provides a powerful, declarative paradigm for designing, building, and analyzing complex systems where human insight and machine intelligence collaborate. Define your *what*, and let Skeptofox orchestrate the *how*.
### Key Features
* **Declarative by Design:** Define complex workflows with intuitive, human-readable abstractions instead of writing brittle, imperative code.
* **Agentic AI Primitives:** High-level abstractions for bundling and linking single or multi-agent systems with data and automation pipelines.
* **Human-in-the-Loop:** Built-in hooks for human validation, feedback, and interactive steering of automated processes.
* **Extensible & Composable:** Easily integrate custom tools, models, data sources and endpoints from other pipelines into this self-orchestrating framework.
### Installation
```bash
pip install skeptofox
```
### Quick Start
Here's a simple example of defining a research agent that drafts a report and asks for human approval before finalizing it.
```python
from skeptofox import Workflow, Agent, HumanValidationStep, tool
# Define a simple tool for the agent to use
@tool
def web_search(query: str) -> str:
"""Performs a web search and returns the top results."""
# (Your search implementation here)
print(f"--> Searching for: {query}")
return "Skeptofox was created in 2025. It focuses on declarative AI."
# 1. Define the Agent's identity and tools
researcher = Agent(
role="Expert Tech Analyst",
goal="Find information about the Skeptofox library and draft a summary.",
tools=[web_search]
)
# 2. Declaratively define the workflow
wf = Workflow(
name="Tech Report Workflow",
steps=[
researcher.plan("Create a plan to research Skeptofox."),
researcher.execute("Execute the research plan."),
HumanValidationStep(
prompt="Please review the draft summary. Approve or provide feedback."
),
researcher.execute("Finalize the report based on human feedback."),
],
)
# 3. Run the workflow
if __name__ == "__main__":
final_report = wf.run()
print("\n--- Final Report ---")
print(final_report)
```
### Documentation
For detailed guides and API references, please see our full documentation (link coming soon).
### Contributing
Contributions are welcome! Whether it's bug reports, feature requests, or new code, please see our `CONTRIBUTING.md` guide for details on how to get started.
### License
This project is licensed under the MIT License. See the `LICENSE` file for details.
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"description": "# skeptofox\n\n\n\n\n\nskeptofox provides a powerful, declarative paradigm for designing, building, and analyzing complex systems where human insight and machine intelligence collaborate. Define your *what*, and let Skeptofox orchestrate the *how*.\n\n\n### Key Features\n\n* **Declarative by Design:** Define complex workflows with intuitive, human-readable abstractions instead of writing brittle, imperative code.\n* **Agentic AI Primitives:** High-level abstractions for bundling and linking single or multi-agent systems with data and automation pipelines.\n* **Human-in-the-Loop:** Built-in hooks for human validation, feedback, and interactive steering of automated processes.\n* **Extensible & Composable:** Easily integrate custom tools, models, data sources and endpoints from other pipelines into this self-orchestrating framework.\n\n### Installation\n\n```bash\npip install skeptofox\n```\n\n### Quick Start\n\nHere's a simple example of defining a research agent that drafts a report and asks for human approval before finalizing it.\n\n```python\nfrom skeptofox import Workflow, Agent, HumanValidationStep, tool\n\n# Define a simple tool for the agent to use\n@tool\ndef web_search(query: str) -> str:\n \"\"\"Performs a web search and returns the top results.\"\"\"\n # (Your search implementation here)\n print(f\"--> Searching for: {query}\")\n return \"Skeptofox was created in 2025. It focuses on declarative AI.\"\n\n# 1. Define the Agent's identity and tools\nresearcher = Agent(\n role=\"Expert Tech Analyst\",\n goal=\"Find information about the Skeptofox library and draft a summary.\",\n tools=[web_search]\n)\n\n# 2. Declaratively define the workflow\nwf = Workflow(\n name=\"Tech Report Workflow\",\n steps=[\n researcher.plan(\"Create a plan to research Skeptofox.\"),\n researcher.execute(\"Execute the research plan.\"),\n HumanValidationStep(\n prompt=\"Please review the draft summary. Approve or provide feedback.\"\n ),\n researcher.execute(\"Finalize the report based on human feedback.\"),\n ],\n)\n\n# 3. Run the workflow\nif __name__ == \"__main__\":\n final_report = wf.run()\n print(\"\\n--- Final Report ---\")\n print(final_report)\n```\n\n### Documentation\n\nFor detailed guides and API references, please see our full documentation (link coming soon).\n\n### Contributing\n\nContributions are welcome! Whether it's bug reports, feature requests, or new code, please see our `CONTRIBUTING.md` guide for details on how to get started.\n\n### License\n\nThis project is licensed under the MIT License. See the `LICENSE` file for details.",
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