Fast Research

Fast Research Skill

Use this skill for a rapid, evidence-grounded literature brief when the user needs quick scientific orientation without sacrificing traceability.

If the user later asks an exact follow-up question about one of the downloaded local papers, use pageindex-grounded for that bounded grounded retrieval step instead of treating this search workflow as the final QA layer.

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/fast-research/SKILL.md \
  -o SKILLS/fast-research/SKILL.md

Mission

Given a research question, use papercli to:

1. Search relevant papers.
2. Download a focused core set of PDFs.
3. Read enough content to extract core ideas, concepts, and key equations.
4. Produce a detailed findings.md report inside the active research run folder, with inline references tied to exact papers.
5. Produce a companion literature-map block diagram that shows how the selected papers connect.

Prerequisites

• papercli is installed and available in PATH.

Required Inputs

• Research question or hypothesis.
• Optional scope constraints: years, domain, must-include authors, method family.

If inputs are missing, infer a minimal scope and proceed.

Hard Requirements

• Always use papercli for retrieval (search, info, download).
• Download and read papers, not just metadata.
• Every factual claim must be grounded by references.
• Include key math when present in papers.
• Final output must be a markdown file named findings.md inside the active research run folder.
• Each distinct topic must live in its own dated, topic-slugged folder under research/.
• Maintain research/INDEX.md and the run-local RUN.md metadata file so later agents can recognize what each research folder contains.
• After synthesis, produce a companion literature-map diagram through the shared block-diagram skill.
• The literature map must only show evidence-backed relations such as method lineage, direct comparison, shared benchmark or dataset, critique, or common problem framing.
• Do not invent paper-to-paper influence or citation edges that are not supported by the corpus.
• OpenColab normally provides OPENCOLAB_PROGRESS_FILE during provider runs. When it is set, emit bounded JSON progress updates for long-running stages instead of remaining silent until the end.

OpenColab Progress Helper

OpenColab exposes this progress channel by default during provider runs. When OPENCOLAB_PROGRESS_FILE is available, use this helper:

emit_progress() {
  if [ -z "${OPENCOLAB_PROGRESS_FILE:-}" ]; then
    return 0
  fi
  printf '%s\n' "$1" >> "$OPENCOLAB_PROGRESS_FILE"
}

Write one-line JSON events. Allowed kind values are started, progress, milestone, warning, needs_input, and completed.

Example:

emit_progress '{"kind":"progress","stage":"download","slot":"search","current":8,"total":12,"message":"Downloaded 8 of 12 PDFs."}'

Let the agent decide what is worth sending. Use progress for countable ongoing work, milestone for stage changes, warning for degraded runs, needs_input for blockers, and completed when an explicit completion event helps. Do not narrate every minor command.

Topic-Scoped Research Workspace

Every run must use an active run root:

• New topic: research/<YYYY-MM-DD>-<topic-slug>/.
• Topic slug: lowercase ASCII, hyphenated, 3-8 meaningful words, and specific enough to distinguish the topic from nearby research.
• Collision rule: if the folder exists for different work, append -2, -3, or another short disambiguator.
• Continuation rule: reuse an existing folder only when the user asks to continue the same topic or the folder clearly matches the current request.
• Root catalog: update research/INDEX.md when the run starts and again when it finishes, is blocked, or is left partial.
• Run metadata: create and update <RUN_ROOT>/RUN.md with topic, question, skill, status, created/updated timestamps, corpus counts, generated artifact paths, and follow-up notes.

Recommended research/INDEX.md columns:

| Folder | Skill | Topic | Status | Created | Updated | Corpus | Deliverables | Notes |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |

Recommended <RUN_ROOT>/RUN.md headings:

# Research Run: <topic>

## Metadata

- Skill: fast-research
- Status: in-progress
- Created:
- Updated:
- Topic slug:
- Question:

## Corpus

- Selected:
- Downloaded:
- Summarized:
- Failure events:

## Artifacts

- Findings:
- Literature map:
- Search files:
- Metadata:
- PDFs and summaries:

## Notes

Workflow

1. Setup topic-scoped workspace

TOPIC_SLUG="<topic-slug>"
RUN_ROOT="research/$(date +%F)-${TOPIC_SLUG}"
mkdir -p "$RUN_ROOT"/{search,meta,pdf,diagrams}
printf "stage\tid\treason\n" > "$RUN_ROOT/meta/failures.tsv"
: > "$RUN_ROOT/meta/downloaded_ids.txt"
: > "$RUN_ROOT/meta/summarized_ids.txt"

Before retrieval, add or update the row for $RUN_ROOT in research/INDEX.md with status in-progress, and create or update $RUN_ROOT/RUN.md.

Initialize config when needed:

papercli config init

2. Run fast retrieval pass

Use one tight query and one alternate phrasing:

papercli search "<query>" \
  --provider all \
  --sort relevance \
  --limit 15 \
  --format json \
  --out "$RUN_ROOT/search/seed.json"

papercli search "<alternate query>" \
  --provider all \
  --sort date \
  --year-from <optional_year> \
  --limit 10 \
  --format json \
  --out "$RUN_ROOT/search/recency.json"

3. Select and enrich 3-6 papers

Prioritize relevance, recency, and diversity of approach.

jq -r '.[].id' "$RUN_ROOT/search/seed.json" "$RUN_ROOT/search/recency.json" | \
  awk 'NF && !seen[$0]++' | head -n 6 > "$RUN_ROOT/meta/selected_ids.txt"

For each selected paper, fetch metadata and PDF:

while read -r id; do
  safe_id="$(echo "$id" | tr '/:' '__')"

  if ! papercli info "$id" --provider all --format json --out "$RUN_ROOT/meta/${safe_id}.json"; then
    printf "info\t%s\tmetadata lookup failed\n" "$id" >> "$RUN_ROOT/meta/failures.tsv"
  fi

  if papercli download "$id" --provider all --out "$RUN_ROOT/pdf/${safe_id}.pdf"; then
    printf "%s\n" "$id" >> "$RUN_ROOT/meta/downloaded_ids.txt"
  else
    printf "download\t%s\tpdf download failed\n" "$id" >> "$RUN_ROOT/meta/failures.tsv"
  fi
done < "$RUN_ROOT/meta/selected_ids.txt"

4. Create agent-ready paper summaries

Delegate this step to the paper-summary skill. It owns the canonical summary schema, the Gemini-based batch runner, and the per-paper output contract.

Run the batch summarizer after PDFs and metadata are in place:

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 10

Retry a single failed paper with:

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"

Summary requirements:

• Use the canonical schema in SKILLS/paper-summary/references/summary_schema.md.
• Write each summary to $RUN_ROOT/pdf/<safe_id>.md, next to $RUN_ROOT/pdf/<safe_id>.pdf, unless an explicit output directory is needed.
• Read the PDF directly so figures, captions, tables, equations, and page anchors remain first-class evidence.
• Use metadata only as fallback and label it clearly.
• Record summary failures in $RUN_ROOT/meta/failures.tsv and continue processing the rest of the corpus.

5. Produce findings.md

Target quality: fast but technically useful.

• Include 3-6 referenced papers.
• Provide a compact synthesis of core ideas.
• Include at least 2 key equations from the corpus when available.
• Write math in plain-text markdown, not LaTeX blocks, so the file reads cleanly in raw form and can be parsed by downstream tools.
• Use the per-paper schemas in $RUN_ROOT/pdf/ as the primary synthesis substrate.

6. Produce literature-map block diagram

Delegate this step to the shared block-diagram skill. It owns the canonical D2 source, render, validation, and diagram-file delivery flow.

Diagram requirements:

• Base the diagram on the same corpus and [R#] references used in findings.md.
• Show how the most relevant papers connect through evidence-backed relations only.
• Prefer compact paper-family clusters when a flat per-paper diagram would be noisy.
• Use a topic-derived slug such as <topic-slug>-literature-map under $RUN_ROOT/diagrams/.
• Prefer png as the primary delivered literature-map artifact.
• Keep svg as the editable or fallback artifact when PNG rendering is unavailable.

Output Contract (findings.md)

Use this structure:

# Findings: <topic>

## Scope

- Question: ...
- Coverage window: ...
- Selection criteria: ...
- Corpus stats: selected ..., downloaded ..., summarized ..., failure events ...

## Core Ideas

Claim with inline refs [R1][R3].
Claim with inline refs [R2].

## Key Concepts

- Concept A: definition and role [R1].
- Concept B: definition and trade-off [R2][R4].

## Key Math

Equation: <name> = <plain-text formula> [R3]
Where: <symbol> = <meaning>; ...
Meaning and why it matters [R3].

Equation: <name> = <plain-text formula> [R2]
Where: <symbol> = <meaning>; ...
Meaning and assumptions [R2].

## Paper Notes

### [R1] <title>

- Problem:
- Method:
- Main result:
- Limits:

### [R2] <title>

- Problem:
- Method:
- Main result:
- Limits:

## References

| Ref | Paper    | Provider ID  | Year | Evidence                  |
| --- | -------- | ------------ | ---- | ------------------------- |
| R1  | Title... | arxiv:...    | 2024 | `pdf/...md`, `pdf/...pdf` |
| R2  | Title... | semantic:... | 2023 | `pdf/...md`, `pdf/...pdf` |

Companion literature-map artifacts:

• $RUN_ROOT/diagrams/<topic-slug>-literature-map.d2
• $RUN_ROOT/diagrams/<topic-slug>-literature-map.png
• optional $RUN_ROOT/diagrams/<topic-slug>-literature-map.svg

Final Chat Reply

After writing $RUN_ROOT/findings.md, return a short, friendly summary for the user-facing chat reply. Do not change the findings.md structure to match the chat reply.

• Keep the tone warm and readable, but still evidence-grounded.
• A small number of emojis is fine when it improves scanability. Prefer at most one emoji per line.
• Include:
  • one direct-answer line
  • one corpus-stats line with selected, downloaded, summarized, and failure counts
  • one short literature-map line explaining how the main papers or paper families connect
  • 2-3 short cited takeaways
  • one short limitation or uncertainty line when it materially affects confidence
  • one short closing line that points to $RUN_ROOT/findings.md
• Do not paste large chunks of findings.md into the chat reply.
• If the active channel supports returning files, return findings.md plus the PNG literature-map diagram after the summary. If PNG rendering is unavailable, return the SVG artifact instead.

Referencing Rules

• Use [R#] inline citations in all analytical sections.
• Do not cite claims without evidence.
• For equation-based claims, cite the source paper on the same line.
• Keep quotes short; prefer paraphrase plus citation.

Done Criteria

• findings.md exists and is detailed.
• Claims are referenced.
• Papers were downloaded and read.
• Each selected paper has an agent-ready summary in $RUN_ROOT/pdf/ unless extraction failed.
• Selected, downloaded, and summarized counts reconcile with $RUN_ROOT/meta/selected_ids.txt, $RUN_ROOT/meta/downloaded_ids.txt, and $RUN_ROOT/meta/summarized_ids.txt, and failure events reconcile with $RUN_ROOT/meta/failures.tsv.
• Core ideas, concepts, and key math are covered.
• A PNG literature-map artifact exists, or an SVG fallback is returned when PNG rendering is unavailable, and the diagram only shows evidence-backed cross-paper connections.
• research/INDEX.md and $RUN_ROOT/RUN.md are updated with final status, corpus counts, artifact paths, and any limitations or next-step notes.