Doc Health Metrics: How Two Writers Built a Framework to Prioritize Docs
summary
Creates a measurable docs health system that scores product docs across five concrete metrics — coverage, readability, style compliance, freshness, discoverability — using AI to run Python scripts, YAML configs and two HTML dashboards (about 3500 lines of Python). Produces a DCR percentage, bands (nanoscars → comprehensive), prioritized recommendations with impact/effort/time estimates, and leadership-facing business‑impact mappings; each assessment costs about $50 and runs with a tech‑writer in the loop, and early runs across dozens of products show teams actually act on the prioritized fixes.
AI-written summary · about
chapters (8)
- 0:00Introduction
- 1:08Why docs health matters
- 3:55Five key docs metrics
- 13:24How framework works
- 19:23Reporting for teams
- 21:56Three lessons learned
- 23:21What makes docs healthy
- 25:28Q&A
related talks
20mDo Docs Better: Practical Tips on Delivering...
37mTaking a step back: Analysing your documentation
20mOh My Docs!
45mDocs as Code Fix a poor documentation culture in your organization
29mTaking Stock of Your Documentation
23mWriting Docs Worth Reading
44mCreating a Culture of Documentation
45mDocs or it didn't happen!