The structured model and StructuredCvProfileJson.FromSections already map
Projects/Certifications/Languages headings, but the AI normalize prompt
never emitted them, so on the benchmark CV the entire Projects section and
the in-summary languages (English Native, Norwegian B1) were silently
dropped. This closes that gap upstream — no backend schema or data change.
ai-service (tools/summarizer/app.py):
- /cv/normalize: added # Projects and # Certifications headings; a
languages-from-prose rule (pull "native English", "Norwegian at B1" out
of the summary even with no Languages section; ignore programming
languages); and skill-group prefix stripping ("Development:",
"DevOps & Infrastructure:", "Practices:" dropped, only the skills kept).
- /cv/classify-block: Projects and Certifications added to the section
enum + rules (fallback path).
Backend:
- LooksLikeNormalizedMarkdownCv now recognises # Projects / # Certifications
so those CVs still take the markdown assembly path.
Tests:
- CvExtractionCoverageTests (4) lock the C# mapping of Projects,
Certifications and Languages sections into the structured profile.
- ai-service test_classify_block_supports_projects_section (1).
426 backend tests, 17 ai-service tests pass; app.py compiles.
The LLM behaviour (prompt -> headings) needs Ollama to observe and was not
run here; the C# side that consumes the headings is proven and the prompt
change is additive. Merge-not-replace + the review screen are the next
increment (2.1-a, approved: always-review, conservative merge).
Deployment: these prompts live in the ai-service container, which
deploy.sh does not rebuild by default -- deploy with
DEPLOY_BUILD_AI_SERVICE=true or the change won't take effect.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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