pattern-retrospective

Name: pattern-retrospective
Availability: InStock
Author: Bryce

Extract reusable patterns and improvement proposals from Claude transcripts with provenance.

Updated Jun 16, 2026

Search Tags:#workflow #retrospective #provenance #quality-gate #transcripts #falsification #streaming-jsonl

Ready to run

npx skills add https://github.com/BryceEWatson/claude-global-skills --skill pattern-retrospective

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pattern-retrospective
Source: https://github.com/BryceEWatson/claude-global-skills/tree/main/pattern-retrospective
Command: npx skills add https://github.com/BryceEWatson/claude-global-skills --skill pattern-retrospective

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Pattern-retrospective provides a disciplined framework to mine Claude transcripts for reusable patterns, build evidence-backed retrospectives, and track follow-ups with provenance, improving transparency and reproducibility of insights.

Core Features & Use Cases

Streaming JSONL parsing to extract structure from large transcript datasets without loading entire files.
5-tuple extraction with provenance tags to enable traceable findings and validations.
Falsification and quality gates to ensure reliability before publishing, plus tools to manage follow-ups across projects.
Use Case: an analyst reviews a set of handoff documents to generate a structured retro report and a list of actionable improvements with audit trails.

Quick Start

Run the retro workflow to draft patterns and output a retro report to the project registry.

Frequently Asked Questions about pattern-retrospective

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

FAQPage Schema

How do I extract reusable patterns from Claude transcripts?▼

You can extract reusable patterns from Claude transcripts by running an automated retrospective workflow that performs 5-tuple extraction with provenance tagging, ensuring findings are traceable and validated before publishing.

Can I parse large streaming JSONL transcript files without loading everything into memory?▼

Yes, streaming JSONL parsing processes large transcript datasets incrementally, extracting structured data without loading entire files into memory, enabling analysis of extensive conversation logs efficiently.

How does provenance tagging improve transcript retrospective quality?▼

Provenance tagging enforces traceability by linking extracted 5-tuples to their source transcripts, enabling falsification checks and Bayesian confidence smoothing to ensure credibility before publishing retrospective reports.

What's the best way to generate audit trails for Claude handoff documents?▼

Automated retrospective analysis of handoff documents generates structured retro reports with actionable improvements, enforcing quality gates and provenance tagging to maintain transparent audit trails across projects.

Are there quality gates to validate insights before publishing a retrospective report?▼

Yes, built-in quality gates apply falsification and Bayesian confidence smoothing across transcripts, handoffs, and specs, ensuring extracted patterns meet credibility standards before publishing to the project registry.

When should I use automated retrospective analysis for transcript mining?▼

Use automated transcript mining when you need evidence-backed retrospectives with provenance tracking across multiple handoffs, specs, and improvement docs, ensuring reproducibility and transparency of extracted insights.