mr-fang-vlsi/eda-pdf-local-summary
skills/eda-pdf-local-summary/SKILL.md
Summarize local paper PDFs into structured, citation-grounded evidence notes. Use when the user provides local PDF paths and asks for methods/assumptions/results/limitations extraction or wants evidence mapped to current EDA hypotheses.
$ install --global
skillsauthnpx skillsauth add mr-fang-vlsi/edagent eda-pdf-local-summaryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- eda-pdf-local-summary
- description:
- Summarize local paper PDFs into structured, citation-grounded evidence notes. Use when the user provides local PDF paths and asks for methods/assumptions/results/limitations extraction or wants evidence mapped to current EDA hypotheses.
EDA PDF Local Summary
Overview
Use this skill to produce reusable local summary notes tied to page-level evidence.
Workflow
- Validate input PDF path.
- require absolute or repo-relative local path.
- expected location:
docs/papers/pdf/.
- Extract text to local artifact.
- Run
scripts/extract_pdf_text.sh <pdf_path> <out_dir>. - default output dir:
docs/papers/summaries/raw/. - default extractor priority is
GROBID(viagrobid_client+GROBID_SERVER), then falls back topdftotext/mutool/pypdfif unavailable. - to disable GROBID for one run: set
DISABLE_GROBID=1. - quality guard: if GROBID TEI result is too sparse, extractor auto-falls back to local text extraction.
- when GROBID succeeds, keep TEI artifact alongside text (
<pdf_stem>.tei.xml) for traceability.
- Build structured summary.
- Load
references/summary-template.md. - Fill sections with explicit evidence snippets.
- Prefer page-cited claims (
p.xx) when recoverable from extracted text. - write output to:
docs/papers/summaries/<pdf_stem>.summary.md.
3.5 Update paper manifest status.
- locate corresponding row in
docs/papers/manifests/*.paper_manifest.tsv. - update
local_pdf_pathand setstatus=summarized.
- Sync landscapes after summary write.
- run
python3 scripts/common/paper_landscape_sync.py build. - ensure both landscape docs are updated:
docs/knowledge_base/95_PROBLEM_LANDSCAPE.mddocs/knowledge_base/96_METHOD_LANDSCAPE.md
- Link to active hypothesis.
- State whether paper supports, contradicts, or is neutral to current model/flow hypothesis.
- add one "actionable next experiment" sentence.
Output Contract
Always output:
- extracted text artifact path,
- summary markdown path (
docs/papers/summaries/<pdf_stem>.summary.md), - 3-5 bullet findings with evidence strength (
strong/medium/weak), - unresolved ambiguities requiring manual read,
- updated manifest path (or explicit note if no manifest row matched).
- landscape sync artifact paths (
95/96docs or explicit failure reason).
References
Load:
references/summary-template.mdreferences/evidence-grading.md
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