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CI/Linting: Future improvements for AI-generated content quality #58

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Description

@oskarth

Context

This issue tracks future CI/linting improvements for ensuring quality of AI-generated documentation content. The low-hanging fruit was implemented in #57.

Tier 2: Medium Effort Improvements

1. Vale Prose Linter Integration

Effort: 4-5 hours | Impact: High

  • Professional prose linter with custom IPTF rules
  • Catches: terminology inconsistency, passive voice, hedging language ("might", "could potentially")
  • Files needed:
    • .vale.ini - configuration
    • .vale/styles/IPTF/Marketing.yml - marketing rules
    • .vale/styles/IPTF/Terminology.yml - terms from GLOSSARY.md
    • .vale/styles/IPTF/Hedging.yml - AI hedging patterns

2. Frontmatter Schema Validation (JSON Schema)

Effort: 3-4 hours | Impact: Medium

  • Full schema validation per content type using ajv
  • Catches: invalid enum values, AI-invented frontmatter fields
  • Add schemas: scripts/schemas/{pattern,vendor,use-case,jurisdiction}.json

3. Section Structure Validation for All Content Types

Effort: 2-3 hours | Impact: Medium

  • Extend current pattern-only validation to vendors, use-cases, approaches, jurisdictions
  • Define required sections per type in the validation script

4. GLOSSARY.md Term Consistency Checker

Effort: 4-5 hours | Impact: High

  • Parse GLOSSARY.md, check all files use canonical spellings
  • Catches: "zk-SNARK" vs "zkSNARK", "DVP" vs "DvP"
  • Script: scripts/check-terminology.js

Tier 3: Higher Effort Improvements

5. Pre-commit Hooks

Effort: 3 hours | Impact: High

  • Use husky + lint-staged for fast local checks before commit
  • Run frontmatter, section structure, marketing checks on staged files

6. LLM-Based Content Review (On-Demand)

Effort: 8-12 hours | Impact: High

  • Script using Claude API for:
    • Verifying factual claims against GLOSSARY.md
    • Checking ERC/EIP numbers are real
    • Flagging potential hallucinations
    • Consistency with related documents
  • Not for CI (cost/latency), but for maintainer review

Priority Order

  1. Vale prose linter (high ROI for terminology + style)
  2. Glossary term consistency (catches common AI issues)
  3. Section validation for all types
  4. Frontmatter schemas
  5. Pre-commit hooks
  6. LLM review tool

Related

Activity

  1. oskarth commented on Jan 23, 2026

    @oskarth
    CollaboratorAuthor

    Done! PR #68 adds the full AI content quality guardrails:

    Validation tools:

    • npm run validate - Frontmatter JSON Schema validation for patterns, use cases, vendors, jurisdictions
    • npm run check-terms - GLOSSARY.md terminology consistency checker
    • npm run lint:vale - Vale prose linter with custom IPTF styles
    • npm run llm-review <file> - On-demand Claude-powered content review

    CI integration:

    • GitHub Actions workflow runs validate, check-terms, and Vale on every push
    • Husky pre-commit hooks run checks locally before commit

    Documentation:

    • README.md updated with Development section showing how to run checks

    Follow-up: Created #67 to track fixing the ~300 warnings found by the new guardrails in existing content.

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