skill-episodes-v1

Convert Trace Index skill_invocation units into skill-use episodes.

92|6|Updated Mar 27, 2026

Search Tags:#skill usage #codebase analysis #trace analysis #skill tracking #workflow intelligence

Ready to run

npx skills add https://github.com/JayFarei/opentraces --skill skill-episodes-v1

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skill-episodes-v1
Source: https://github.com/JayFarei/opentraces/tree/main/src/opentraces/workflow_templates/skill-episodes-v1
Command: npx skills add https://github.com/JayFarei/opentraces --skill skill-episodes-v1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses the challenge of converting Trace Index invocations into structured, reviewed episodes for analysis and workflow tracking.

Core Features & Use Cases

Trace Index Processing: Projects skill_invocation units from the Trace Index into skill-use episodes.
Workflow Projections: Generates rows for local workflow skills from the Trace Index, without the need for a separate skill ledger.
Use Case: Consider a scenario where you want to track and analyze the usage of specific skills across different codebases. This Skill would help in compiling those interactions into episodes for further review and analysis.

Quick Start

Build skill-episodes-v1 rows from the Trace Index with the following command: python scripts/build_rows.py --output /path/to/output.

Frequently Asked Questions about skill-episodes-v1

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

FAQPage Schema

How do I convert Trace Index skill invocations into structured episodes for analysis?▼

To convert Trace Index skill invocations into structured episodes, you can use a script that projects `skill_invocation` units into `skill-use` episodes, maintaining workflow consistency with the core index for trace analysis.

What is the best way to track skill usage across different codebases without a separate skill ledger?▼

The best way to track skill usage across codebases without a separate skill ledger is by generating local workflow skill rows directly from the Trace Index, projecting invocations into reviewable episodes.

How do I build skill-use rows from the Trace Index for workflow intelligence?▼

You build skill-use rows from the Trace Index for workflow intelligence by running a Python script with an output path argument, which processes the trace data into structured episodes.

Do I need a separate skill ledger to analyze skill usage from the Trace Index?▼

No, you do not need a separate skill ledger to analyze skill usage from the Trace Index; you can generate rows for local workflow skills directly from the Trace Index itself.

Can I use opentraces consumers for maintaining workflow consistency in trace analysis?▼

Yes, you can use `opentraces.consumers.skill_intelligence` to maintain workflow consistency with the core index when transforming Trace Index invocations into skill-use episodes.

What are the limitations of processing Trace Index invocations into skill-use episodes?▼

A limitation of processing Trace Index invocations into skill-use episodes is that it specifically requires `skill_invocation` units as input and depends on `opentraces.consumers.skill_intelligence` for workflow consistency.