FrontierScholar 知沿学术
A research wiki of about 1.01M computer-science arXiv papers, built for coding agents. Papers are organised into domains, topics and subtopics; each subtopic has pages on its research problems, method families, datasets and benchmarks, and a frontier page of open gaps and rising approaches. Every claim points back to arXiv ids.
This repository has the fs command-line client and the fs-cli agent skill.
Website and API documentation: https://frontier-scholar.com.
Install
pip install frontier-scholar # Python 3.8+, no dependencies
fs --version # CLI and API versions, data snapshot
fs talks to the public endpoint https://frontier-scholar.com and needs no key (see Limits).
Agent skill
skills/fs-cli/ tells a coding agent (Claude Code, Codex, Cursor, Gemini CLI, pi, ...) when and how to use fs:
npx skills add FrontierScholar/FrontierScholar
# or
gh skill install FrontierScholar/FrontierScholar
or copy skills/fs-cli/ into your agent's skills folder. Then ask in plain language, e.g. "Use fs: what are the open
problems of adaptive retrieval, and which approaches are rising?"
Commands
| Command | What it does |
|---|---|
fs select "QUERY" |
The next level of the tree (domains, topics, subtopics), ranked by a query |
fs search paper "QUERY" |
Papers ranked by title, abstract and dataset names; --before / --after dates |
fs search wiki [index|pages|frontier|bench] "QUERY" |
Subtopic overviews, problem / method / resource pages, frontier gaps and trends, benchmarks |
fs read TARGET... |
A paper (original abstract, date, subtopics), a paper's pages, wiki pages, folders, a subtopic's papers |
fs related ID... |
Papers the wiki groups with the given ones |
fs meta [wiki|dates] ID... |
Titles and dates, subtopics, first-version date checks |
fs select "adaptive retrieval" --topk 3
fs search paper "adaptive retrieval" --before 2025-01-01
fs search wiki frontier "adaptive retrieval" --status open
fs read 2601.04618
fs meta dates 2601.04618 2604.15621 --before 2026-06-01
Answers are JSON (wiki pages print as Markdown). They are lookups and keyword (BM25) rankings over one fixed data
snapshot: nothing is generated. Wiki pages are summaries written from the papers; the only original text is a paper's
abstract. fs COMMAND -h lists every option and output field.
From Python:
from frontier_scholar import Client
r = Client().call("search/paper", {"query": "adaptive retrieval", "topk": 5})
for p in r["items"]:
print(p["paper_id"], p["date"], p["title"])
The HTTP API is POST https://frontier-scholar.com/api/v1/fs/<command> with the arguments as JSON; see the
documentation.
Limits
Without a key, each IP gets 10 requests a minute and 300 a day, and calls are smaller (--topk up to 20, read up to
5 targets, meta up to 50 ids, no --grep); curl https://frontier-scholar.com/api/v1/fs/quota shows what is left.
With a key from the FrontierScholar team, set FS_API_KEY (in the environment, never in code); calls then use that
account's limits. FS_BASE points fs at another service.
Layout
src/frontier_scholar/ the fs CLI and its client (standard library only)
skills/fs-cli/ the agent skill: SKILL.md, references/, CHANGELOG.md
tests/ CLI tests
The earlier frontier-scholar SDK and skills are on the legacy-sdk branch.
License
Apache-2.0, see LICENSE.
Metadata
Release files for frontier-scholar 1.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| frontier_scholar-1.2.2.tar.gz | 20.1 kB | Without provenance | Details for frontier_scholar-1.2.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| frontier_scholar-1.2.2-py3-none-any.whl | Python 3 | none | any | Details for frontier_scholar-1.2.2-py3-none-any.whl |
Total release size: 39.0 kB
Release files / frontier_scholar-1.2.2.tar.gz
| Download URL | frontier_scholar-1.2.2.tar.gz |
|---|---|
| Size | 20.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.12.7
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Release files / frontier_scholar-1.2.2-py3-none-any.whl
| Download URL | frontier_scholar-1.2.2-py3-none-any.whl |
|---|---|
| Size | 18.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.7
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