tasks.org.ai: Refactor parser to use graphdl correctly and all 217 verbs

[nathanclevenger]

Problem

The O*NET task parser in ai/packages/tasks.org.ai/src/parser-graphdl.ts has several architecture issues:

1. Duplicate Casing Logic

• tasks.org.ai/src/casing.ts duplicates toPascalCase and toCamelCase functions
• graphdl/src/casing.ts already exports these same functions
• Should: Import from graphdl instead of duplicating

2. Hardcoded Verbs (63 instead of 217)

• isLikelyVerb() function has only 63 hardcoded verbs (lines 62-129)
• All 217 verbs exist in ai/sources/verbs/*.mdx with complete conjugation data
• Should: Import verb list from a verbs.org.ai package or loader module

3. Hardcoded Prepositions

• Parser has 23 hardcoded prepositions (lines 17-41)
• Should: Import from prepositions.org.ai package (if it exists)

4. Parser-Specific Logic (Correct)

• O*NET task parsing logic (extracting components, cleaning phrases, handling alternatives) is appropriate in tasks.org.ai
• This is package-specific transformation, not general-purpose logic

Recommended Architecture

// graphdl (shared core) - ALREADY HAS:
- toCamelCase, toPascalCase, toKebabCase
- toThirdPerson, toEvent, toActivity, toSubjectNoun, toObjectNoun, toInverse

// verbs.org.ai package (NEW) - SHOULD HAVE:
- export const VERBS: Set<string> = new Set([...217 verb names])
- export const VERB_CONJUGATIONS: Map<string, VerbConjugation>
- export function isVerb(word: string): boolean

// prepositions.org.ai package (if exists) - SHOULD HAVE:
- export const PREPOSITIONS: Set<string>

// tasks.org.ai (package-specific) - KEEP:
- parseGraphDL() - O*NET-specific parsing logic
- cleanObjectPhrase() - O*NET-specific cleanup
- expandAlternatives() - O*NET-specific handling
- BUT IMPORT: casing from graphdl, verbs from verbs.org.ai, prepositions from prepositions.org.ai

Action Plan

1. Create verb loader module to read all 217 verbs from ai/sources/verbs/*.mdx
2. Export verb utilities from verbs.org.ai package
3. Remove tasks.org.ai/src/casing.ts and import from graphdl instead
4. Update isLikelyVerb() to use complete verb ontology (217 verbs)
5. Check if prepositions.org.ai exists or create loader for it
6. Keep O*NET-specific parsing logic in tasks.org.ai
7. Test parser with full verb list
8. Commit to ai/ submodule

Benefits

• DRY: Eliminates duplicate casing logic
• Complete: Uses all 217 verbs instead of 63
• Maintainable: Single source of truth for verbs in ai/sources/verbs/
• Correct Architecture: Parser uses graphdl utilities, packages don't reinvent the wheel

Files to Modify

• ai/packages/tasks.org.ai/src/parser-graphdl.ts - Import casing from graphdl, import verbs from verbs.org.ai
• ai/packages/tasks.org.ai/src/casing.ts - DELETE (use graphdl instead)
• ai/packages/verbs.org.ai/src/index.ts - ADD verb loader and utilities
• ai/packages/tasks.org.ai/package.json - Add dependency on verbs.org.ai

Context

This came up when investigating whether O*NET tasks are properly semantically parsed. The parser works, but only uses 63 hardcoded verbs when we have 217 fully conjugated verbs available in ai/sources/verbs/.