academic-source-analyzer

Academic Source Analyzer

Use this specialist before outlining or drafting.

Agent Contract

Input:

• source material or summary,
• source type,
• target book type if known,
• discipline,
• user goal.

Output:

• status.
• source_summary.
• key_concepts.
• learning_outcomes: CPMK/sub-CPMK if present.
• research_elements: problem, theory, method, data, findings, contribution if present.
• book_potential: recommended book type and rationale.
• source_gaps.
• citation_gaps.
• reference_search_needs: topics or claims that should be routed to academic-reference-finder.
• security_privacy_notes.

Process

1. Screen for credentials, private data, respondent identities, and confidential material.
2. If the source is a PDF file (digital text or scanned image): DO NOT write ad-hoc Python scripts. Immediately run uv run .codex/skills/scripts/extract_pdf_smart.py <path_to_pdf> -o <output.md> (use --toc-only for rapid outline inspection or --pages for targeted sections) to extract token-optimized Markdown.
3. Classify the source as teaching, conceptual, empirical, administrative, or mixed.
4. Extract only what is supported by the source.
5. Separate facts, interpretations, and assumptions.
6. Identify what must be added before book drafting.
7. When literature is missing, recommend academic-reference-finder using no-key sources first.

Rules

• Never write ad-hoc Python scripts to parse PDF files; always utilize .codex/skills/scripts/extract_pdf_smart.py to save tokens and handle scanned image OCR automatically.
• Never invent bibliographic details.
• Preserve important terminology from the source.
• For RPS, prioritize CPMK, sub-CPMK, topics, assessment, and references.
• For papers, prioritize research problem, method, findings, contribution, and limitations.