file-save-protocol

Write analysis results as JSON and Markdown to a specified output_path.

33|10|Updated Jan 6, 2026
One-click install
npx skills add https://github.com/orientpine/honeypot --skill file-save-protocol
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: file-save-protocol
Source: https://github.com/orientpine/honeypot/tree/main/plugins/investments-portfolio/skills/file-save-protocol
Command: npx skills add https://github.com/orientpine/honeypot --skill file-save-protocol

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analysis workflows risk data loss and hallucination when results are not persisted. This skill defines a strict file-save protocol that ensures every analysis result is written to disk using the Write tool, recording both JSON and markdown summaries for auditing and reproducibility.

Core Features & Use Cases

  • Enforces mandatory persistence of analysis outputs to a coordinator-provided output_path.
  • Generates JSON data alongside a human-readable Markdown summary for quick reviews and audits.
  • Use Case: In multi-agent analysis, each step writes its outputs and validation artifacts to a shared folder, enabling session resumption and traceability.

Quick Start

Save the latest analysis result to the specified output_path and verify the write operation succeeds.

Frequently Asked Questions about file-save-protocol

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I ensure analysis results are saved reliably to disk?

To ensure analysis results are saved reliably, apply a strict file-save protocol that writes outputs to a specified path using the Write tool, verifying success and returning a structured FAIL response with details if the operation fails.

Why save analysis outputs in both JSON and Markdown formats?

Saving analysis outputs in both JSON and Markdown generates structured data alongside a human-readable summary, enabling quick reviews and auditing while ensuring reproducibility across end-to-end workflows.

How to prevent data loss in multi-agent analysis workflows?

Prevent data loss in multi-agent analysis workflows by enforcing mandatory persistence, where each step writes validation artifacts and outputs to a shared folder, enabling session resumption and traceability.

What happens when writing analysis results to an output_path fails?

When writing analysis results to an output_path fails, the file-save protocol returns a structured FAIL response containing specific failure details, ensuring errors are captured during the disk write operation.

Do I need a coordinator to specify the output_path for saving analysis data?

Yes, the file-save protocol persists outputs to a coordinator-provided output_path, ensuring the analysis results are written to the correct designated location for auditing and reproducibility.