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Compute Firefox Knowledge Wiki usage metrics from JSONL logs.

1|Updated Apr 5, 2026
Search Tags:#analytics#logs#metrics#coverage#wiki#triage
One-click install
npx skills add https://github.com/alastor0325/firefox-wiki-plugin --skill stats-alastor0325
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stats
Source: https://github.com/alastor0325/firefox-wiki-plugin/tree/main/skills/stats
Command: npx skills add https://github.com/alastor0325/firefox-wiki-plugin --skill stats-alastor0325

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill turns Firefox Knowledge Wiki logs into clear usage metrics so you can tell whether the wiki is actually helping investigations, where it is being read, and where coverage is weak.

Core Features & Use Cases

  • Usage Analysis: Computes hit rate, ingest coverage, false confidence rate, add activity, and per-skill consultation coverage from wiki and triage logs.
  • Content Prioritization: Identifies the most consulted pages, never-read pages, and documentation gaps tied to components that appear in investigations but not in the index.
  • Operational Review: Supports monthly health checks for teams maintaining a shared knowledge base and helps decide what to rewrite, add, or verify next.

Quick Start

Run the stats analysis for the Firefox Knowledge Wiki and summarize the report with the most urgent recommendation.

Frequently Asked Questions about stats

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

FAQPage Schema
How do I analyze wiki log data to measure knowledge base usage and effectiveness?▼

Wiki log data analysis measures knowledge base usage by reading JSONL logs to aggregate per-skill and per-page metrics. It computes hit rate, ingest coverage, and false confidence rate to evaluate whether the wiki actively supports investigations.

What is the best way to identify documentation coverage gaps from triage logs?▼

Identifying documentation coverage gaps from triage logs involves matching components appearing in investigations against the wiki index. This highlights never-read pages and missing entries tied to components lacking documentation, guiding what to add or rewrite next.

How do I generate monthly health reports for a shared knowledge wiki?▼

Monthly health reports for a shared knowledge wiki are generated by aggregating add activity and per-skill consultation coverage from JSONL logs. The computed results provide a concise operational review to help teams decide what to verify or rewrite next.

Can I compute false confidence rate and consultation coverage without external dependencies?▼

Computing false confidence rate and consultation coverage requires no external dependencies. The analysis reads JSONL log data directly, aggregating triage patterns and per-skill metrics to evaluate wiki effectiveness and investigation support independently.

Why does my wiki coverage analysis show high ingest coverage but low hit rate?▼

High ingest coverage with low hit rate in wiki coverage analysis indicates that while pages exist for indexed components, they are rarely consulted during investigations. Aggregating per-page metrics from JSONL logs identifies these never-read pages as rewrite candidates.

What metrics should I track for Firefox Knowledge Wiki triage pattern review?▼

Firefox Knowledge Wiki triage pattern review tracks hit rate, false confidence rate, add activity, and per-skill consultation coverage. Aggregating these metrics from JSONL logs reveals investigation workflows and identifies urgent coverage gaps requiring documentation updates.

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