# Crw Research

> Find ALL the arXiv papers that answer a research question, using fastCRW's Firecrawl-compatible Research API. Use when the ask is to survey a literature, enumerate papers on a topic, find what a paper compares against or builds on, list the best models on a benchmark, or recover a paper from a vague description — "papers that do X", "what does X benchmark against", "best open model on Y", "find the paper that ...". Reaches 61.0% recall on the ArXivQA benchmark vs Firecrawl's Research Index 53.3%.

- Skill: `us/crw-research` (Agent Skill)
- Install (CLI): `npx skillmds@latest add us/crw-research`
- Raw SKILL.md: https://api.skillmd.com/api/skills/us/crw-research/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: AGPL-3.0
- Author: us (https://skillmd.com/u/us)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/us/crw-research

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# fastCRW Research

Find EVERY arXiv paper that answers a research query. Recall = union of arXiv
ids; extra ids never hurt, so cast wide but on-topic. The
[Research API](https://docs.fastcrw.com/research-api) is a live, drop-in
Firecrawl-research-compatible surface — your job is **query strategy + intent
routing**, the endpoints do the retrieval.

This skill reaches 61.0% recall on the 191-question ArXivQA benchmark, a number
fastCRW measured directly. Firecrawl publishes 53.3% for its own Research Index
on the same benchmark in their [Research Index launch
post](https://www.firecrawl.dev/blog/research-index-launch) (2026-06-17): "On
arXivQA, the index hits 53.3% recall at $0.32 per task, against 45.4% for the
next best provider."

Set `FASTCRW_API_KEY` (a `crw_live_…` key from https://fastcrw.com/dashboard).
Base URL `https://api.fastcrw.com`. Every endpoint is a GET; pull arXiv ids out
of `results[].ids.arxiv` / `results[].primaryId`.

```bash
# search: ranked papers for one query
curl -s -H "Authorization: Bearer $FASTCRW_API_KEY" \
  "https://api.fastcrw.com/v1/search/research/papers?query=$(jq -rn --arg q "QUERY" '$q|@uri')&k=40"

# references / citers / similar of a seed paper (citation graph)
curl -s -H "Authorization: Bearer $FASTCRW_API_KEY" \
  "https://api.fastcrw.com/v1/search/research/papers/arxiv:1706.03762/similar?intent=related%20work&mode=references&k=40"
```

## The whole game: classify the query, apply the matching method

**A) ALWAYS (base):** write 8–12 **exact-name** queries — specific method, model,
dataset, and benchmark NAMES, not broad phrases ("MoleculeNet benchmark",
"Uni-Mol", "ChemBERTa", not "molecular embeddings"). Call `search` on each,
union the arXiv ids, rank by how many queries surfaced each id. Exact-name
decomposition is the #1 recall lever — one broad query misses the niche papers.
Then **expand**: take the 5 ids the most queries agreed on and pull
`/papers/arxiv:<id>/similar?mode=references` for each, appending any new ids
below the union. This second pass is not optional and is not the same as (B):
it runs on EVERY query type, and it is where the papers that no query names
directly come from.

**B) COMPARE-AGAINST** ("what does X compare to / build on / baseline against")
→ resolve X to its arXiv id, then `/papers/arxiv:<X>/similar?mode=references`.
The answer lives in X's own bibliography.

**C) USING / EXTENDING X** ("models that USE/adopt X") →
`/similar?mode=citers` (forward citations) + exact-name searches for known
adopters.

**D) BEST-ON-BENCHMARK** ("which models score best on X", "largest open model")
→ search the leaderboard, read the OPEN model names
(DeepSeek/Qwen/GLM/Kimi/MiniMax/Llama/Mistral/Gemma — ignore Claude/GPT/Gemini,
no papers), then `search "<model family> technical report"` for each.

**E) NICHE ENUMERATION** ("papers that do X") → exact-name queries (A) are
primary. A tight survey or awesome-list, when on-topic, adds its ids.

## Rules

- Recent ids (25xx / 26xx) are REAL — keep them, never discard as "future-dated".
- A query that sounds specific usually still has a *family* of papers — surface
  the family, don't stop at one. Only a query naming a paper by title is single.
- Merge ALL ids from every step; method-targeted (references/leaderboard) and
  exact-name hits first, broad-search tail after. Never invent ids.