Documentation Quality Metrics
Documentsdocumentation-quality-metricsDocumentation Quality Metrics is an Agent Skill for documents published in the hashgraph-online/awesome-codex-plugins repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.
Audit and measure developer documentation quality using functional quality, structural quality, accessibility, purpose, findability, accuracy, completeness, clarity, concision, consistency, analytics, user goals, doc goals, and metric plans. Use when evaluating docs, designing documentation metrics, selecting dashboards, or linking docs work to user and business outcomes.
How to use this skill
Bring this guide into your coding agent with a prompt tailored to the tool you use.
- Open your project in Codex.
- Copy and paste the prompt below.
- Review files and risks before approving any action.
Inspect the Agent Skill at https://github.com/hashgraph-online/awesome-codex-plugins/blob/HEAD/plugins/LVTD-LLC/skills/skills/documentation-quality-metrics/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/documentation-quality-metrics, but wait for my approval before writing files or running scripts.
Copying this prompt does not install or run the skill. Review third-party files before use.
Documentation Quality Metrics
Use this skill to evaluate developer documentation quality and choose metrics that answer real questions. It combines editorial quality with analytics and user outcomes.
This skill is derived from Docs for Developers: An Engineer's Field Guide to Technical Writing, especially Chapter 9, "Measuring documentation quality." It is expanded with paraphrased guidance from Christopher Gales and the Splunk Documentation Team's The Product Is Docs: Writing Technical Documentation in a Product Development Group, especially Chapter 11, "Measuring Success." Do not copy book prose into user outputs. Source: https://link.springer.com/book/10.1007/978-1-4842-7217-6
Quick Start
- Load
guidelines.mdto choose the smallest useful reference set. - Identify the decision the measurement should support.
- Decide how much uncertainty the team needs to reduce before acting.
- Audit functional quality before structural polish.
- Use
workflows/audit-doc-quality.mdfor a full quality or metric plan. - Prefer metric clusters with baseline and context over isolated numbers.
Default Output
When auditing quality or designing metrics, return:
- Measurement question - what decision the metric or audit supports.
- Uncertainty to reduce - what the team does not know yet and how precise the answer needs to be.
- Functional quality findings - accessibility, purpose, findability, accuracy, completeness.
- Structural quality findings - clarity, concision, consistency.
- Metric plan - qualitative and quantitative signals, baselines, owners, and limits.
- Recommended actions - fixes, experiments, or data collection.
- Caveats - what the available metrics cannot prove.
Contents
| Need | Start Here |
|---|---|
| Understand quality dimensions | references/core/knowledge.md |
| Apply audit and metric rules | references/core/knowledge.md |
| See metric examples | references/core/knowledge.md |
| Run quality audit | workflows/audit-doc-quality.md |
| Route by task | guidelines.md |
Core Posture
- Good docs fulfill their purpose for users.
- Functional quality matters before stylistic polish.
- Metrics reduce uncertainty for a decision; counting is not measurement by itself.
- Combine analytics with qualitative evidence; neither tells the full story alone.