Paper summary

Skill jimezsa/opencolab/projects/SKILLS/paper-summary

🐙 Accelerating Scientific Discovery — Turn your research into an always-on autonomous lab

Install

npx -y skills add jimezsa/opencolab --skill paper-summary

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Deterministic PDF-to-markdown paper summarization for papercli workflows. Given one paper PDF or a directory of paper PDFs, produce schema-conformant markdown summaries and optionally update summarized_ids.txt.

SKILL.md

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Paper Summary Skill

Use this skill when PDFs have already been downloaded and the next step is to create deterministic <run-folder>/pdf/<safe_id>.md summaries from those PDFs.

For precise follow-up QA after the summaries exist, switch to the shared pageindex-grounded skill instead of stretching this skill into ad hoc question answering.

This skill is the canonical summary step for:

SKILLS/fast-research/SKILL.md
SKILLS/pro-research/SKILL.md
SKILLS/deep-research/SKILL.md

Update This Skill

Only do this if the user explicitly asks to update this skill from the GitHub repo.

To refresh this skill directly from the GitHub repo:

curl -fsSL https://raw.githubusercontent.com/jimezsa/papercli/main/SKILLS/paper-summary/SKILL.md \
  -o SKILLS/paper-summary/SKILL.md
curl -fsSL https://raw.githubusercontent.com/jimezsa/papercli/main/SKILLS/paper-summary/references/summary_schema.md \
  -o SKILLS/paper-summary/references/summary_schema.md
curl -fsSL https://raw.githubusercontent.com/jimezsa/papercli/main/SKILLS/paper-summary/scripts/gemini_parallel_summary.py \
  -o SKILLS/paper-summary/scripts/gemini_parallel_summary.py

Mission

Given one paper PDF or a directory of paper PDFs:

Read the PDFs directly with Gemini.
Produce one markdown summary per paper that follows the canonical schema in references/summary_schema.md.
Write each summary as <safe_id>.md, next to <safe_id>.pdf, unless an explicit output directory is provided.
Optionally append original paper IDs to <run-folder>/meta/summarized_ids.txt.

Prerequisites

python3 is installed and available in PATH.
google-genai is installed: python3 -m pip install google-genai
GEMINI_API_KEY is set in the environment.
Network access is available when running the Gemini script.
The PDFs already exist locally.
Optional metadata JSON files exist in <run-folder>/meta/<safe_id>.json.

Required Inputs

A single PDF via --pdf, or a directory of PDFs via --pdf-dir.
Optional --metadata-dir so the script can recover original paper IDs and metadata fallbacks.
Optional --summarized-ids file to append successful original paper IDs.
Optional --failures-tsv file to record summary failures in the same ledger used by the research skills.
The active research run folder, normally research/<YYYY-MM-DD>-<topic-slug>/, when this is called from fast-research, pro-research, or deep-research.

Hard Requirements

Use the canonical schema from references/summary_schema.md unchanged.
Output markdown only. Do not wrap the summary in code fences.
Keep figures, tables, equations, captions, and page anchors as first-class evidence.
Use metadata only as fallback and label it clearly.
If evidence is missing, preserve the required missing-evidence labels instead of guessing.
Do not silently skip failures. Either rerun the paper or record the failure upstream.

Workflow

1. Confirm local inputs

Verify the target PDF exists.
When possible, keep PDF names aligned with the safe_id convention already used by the research skills.
If metadata exists, keep the matching JSON at <run-folder>/meta/<safe_id>.json.

2. Run the Gemini batch summarizer

When this skill is called from a research run, set RUN_ROOT to the active run folder first:

RUN_ROOT="research/<YYYY-MM-DD>-<topic-slug>"

Single paper:

python3 SKILLS/paper-summary/scripts/gemini_parallel_summary.py \
  --pdf "$RUN_ROOT/pdf/<safe_id>.pdf" \
  --metadata-dir "$RUN_ROOT/meta" \
  --summarized-ids "$RUN_ROOT/meta/summarized_ids.txt" \
  --failures-tsv "$RUN_ROOT/meta/failures.tsv"

Batch mode:

python3 SKILLS/paper-summary/scripts/gemini_parallel_summary.py \
  --pdf-dir "$RUN_ROOT/pdf" \
  --metadata-dir "$RUN_ROOT/meta" \
  --summarized-ids "$RUN_ROOT/meta/summarized_ids.txt" \
  --failures-tsv "$RUN_ROOT/meta/failures.tsv" \
  --concurrency 4

Useful flags:

--model <name>: override the default Gemini model.
--output-dir <dir>: write summaries somewhere other than next to the PDFs.
--overwrite: regenerate existing .md summaries.
--concurrency <n>: lower this if the API starts rate limiting.

3. Review outputs

Each successful run should create <run-folder>/pdf/<safe_id>.md.
Check that the output preserves the canonical headings and evidence anchors.
If a paper failed, inspect stderr, then rerun just that paper or keep the failure recorded in <run-folder>/meta/failures.tsv.

Output Contract

One markdown summary per processed PDF.
Each summary follows the canonical schema in references/summary_schema.md.
Successful runs may append the original paper ID to <run-folder>/meta/summarized_ids.txt when metadata is available.

Canonical Assets

Summary schema: SKILLS/paper-summary/references/summary_schema.md
Batch summarizer: SKILLS/paper-summary/scripts/gemini_parallel_summary.py