academic-research

Lingtai-AI/lingtai · Agent Skill

Searches and downloads academic papers, analyzes citations, and writes LaTeX manuscripts.

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Overview

PublisherLingtai-AIOrganization
RepositoryLingtai-AI/lingtai ↗
Skill folderacademic-research
Stars698
Bundled files25
LicenseApache-2.0
Last updatedAugust 14, 2026
LinksSkill source ↗ · Repository ↗

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medium risk · 2 points need attention
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needs extra software
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Installation

A skill is a folder with a SKILL.md file. Pick your agent and run the commands in a terminal (macOS, Linux or Git Bash on Windows) from your project root.

Copy the prompt into Claude, Codex or another assistant: it will review the skill and install it for you.

Install the “academic-research” skill from mozgi.io (https://mozgi.io/skills/academic-research/) for me.

1. Download the archive: https://mozgi.io/skills/academic-research/download
   If it fails, take the skill folder from the source: https://github.com/Lingtai-AI/lingtai/tree/main/tui/internal/preset/skills/swiss-knife/reference/academic-research
2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me.
3. Put the “academic-research” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.).
4. Make sure <skills folder>/academic-research/SKILL.md exists.
5. Briefly tell me what this skill does and offer to try it on my task.

If you cannot do a step yourself, tell me what to click or type.

Review the source files

25 files Download Zip

Read SKILL.md and any companion files before deciding whether to install. Click a file to preview it.

SKILL.md contents

Original author text · read-only

Academic Research

> Nested swiss-knife reference. A modular skill: try the bundled script

> first, then load specific reference files only when you need to escape it.

Try this first

For 80% of "get me this paper" requests, the bundled script is the right answer.

It walks the open-access ladder, falls back automatically, and writes a manifest

the next session can resume from.

# Fetch by any identifier
python3 <skill-path>/scripts/fetch_paper.py 10.1103/PhysRevLett.125.015001
python3 <skill-path>/scripts/fetch_paper.py arXiv:2301.00001
python3 <skill-path>/scripts/fetch_paper.py PMID:12345678

# Batch (one identifier per line in the file)
python3 <skill-path>/scripts/fetch_paper.py --batch dois.txt --out papers/

# Resolve metadata only (no PDF download)
python3 <skill-path>/scripts/fetch_paper.py 10.1038/nature12373 --dry-run

# Skip LibGen (e.g. legal-sensitive environment)
python3 <skill-path>/scripts/fetch_paper.py <id> --no-libgen

Output layout (idempotent — re-runs skip entries with status: ok):

papers/{first-author-year-firstword}/
├── paper.pdf  |  paper.md      # full-text artifact
├── metadata.json                # CrossRef-normalized
└── manifest.json                # {status, tier, source, ts, doi}

Tier ladder (script stops at first hit):

| Tier | Source | Best for |

|------|--------|----------|

| 1 | arXiv direct | Preprints (physics, CS, math, q-bio, econ) |

| 2 | Unpaywall | Publisher-blessed gold/green OA |

| 3 | Europe PMC | Biomedical full-text + PMC mirror |

| 4 | CORE | Institutional repositories (needs $CORE_API_KEY) |

| 5 | Publisher-page extract | Nature/APS/AIP/IOP/Cambridge → in-house extractor (stdlib + requests, no third-party deps). Fetches the already-accessible official article / DOI landing page and parses citation_* metadata + the article body into structured Markdown. No paywall/CAPTCHA bypass, no cookies/credentials — official pages only. A login/paywall page is a clean miss; the ladder then falls through. Opt out with --no-publisher-extract. |

| 5b | Authorized publisher | Licensed/institutional access only — official DOI landing page → same-host publisher PDF → %PDF- validation, full provenance. Recovers paywalled-but-subscribed papers without shadow libraries. Never bypasses paywalls or handles credentials. Opt out with --no-institutional. See authorized-publisher-access.md ↗. |

| 6 | LibGen | Last resort; opt out with --no-libgen |

Set $LINGTAI_RESEARCH_EMAIL to a real address before first use — Unpaywall

rejects placeholder emails with HTTP 422. The default falls back to

[email protected] with a warning.

Read on only if: the script fails on your paper, you need a custom query shape,

or you're composing a multi-step workflow (search → fetch → cite → write).

Before drafting citation-bearing academic writing

> Verify sources before you write prose. If you are about to draft a paper,

> related-work section, literature review, References list, or any author–year /

> citation-bearing manuscript, pass the evidence-verification gate first:

> reference/evidence-verification-gate.md ↗.

> No verified evidence → no confident prose. Peer-reviewed and preprint sources

> must not share the same evidence layer; search results are leads, not citations.

> If the user asks to "go fast," reduce *scope*, not *verification*. Produce a

> verified literature matrix before any submission-like draft.

Escape hatch — quick paths

I'm about to write a paper / references / related-work section → reference/evidence-verification-gate.md (verify FIRST)
The user wants a "fast" / "readable" paper draft → reference/evidence-verification-gate.md (reduce scope, not verification)
I have a DOI                → reference/api-doi-resolver.md → api-crossref.md
I have an arXiv ID          → reference/api-arxiv.md (direct PDF link)
I have a PMID               → reference/api-europe-pmc.md
I have a bibcode            → reference/api-nasa-ads.md (requires free key)
I only have keywords        → reference/decision-tree.md → pick API by discipline
I need a citation network   → reference/api-semantic-scholar.md (single paper) or api-semantic-scholar-batch.md (large corpus) or api-openalex.md
I need to override the PDF ladder → reference/pipeline-obtain-pdf.md
Tier-5 publisher-extract failed and I want to retry it manually → reference/publisher-page-extraction.md
OA + authorized-publisher failed and I have a batch + the user's Zotero → reference/zotero-institutional-fulltext-handoff.md
All OA chains failed        → reference/libgen-fallback.md (last resort)
I need astrophysics         → reference/api-nasa-ads.md
I need high-energy physics  → reference/api-inspire-hep.md
I need biomedical           → reference/api-europe-pmc.md or api-pubmed.md
I need to write/compile a paper → reference/pipeline-latex-writing.md
My empirical draft keeps getting reframed / reviewers "agree" → reference/anti-pattern-text-consistency-vs-data-correspondence.md
I hit an API error          → reference/error-handling.md

Reference index

API references (13)

Each card includes endpoint parameters, runnable code, response shape, rate limits, and fallbacks.

| API | File | Best for | Key? |

|-----|------|----------|------|

| arXiv | api-arxiv.md ↗ | Preprint retrieval | No |

| CrossRef | api-crossref.md ↗ | DOI metadata, funder queries | No (mailto recommended) |

| DOI Resolver | api-doi-resolver.md ↗ | Batch DOI → structured citation | No |

| OpenAlex | api-openalex.md ↗ | Discovery, institution/concept analysis | No |

| Semantic Scholar | api-semantic-scholar.md ↗ | Citation networks, TLDR | No (tight limits) |

| Semantic Scholar Batch | api-semantic-scholar-batch.md ↗ | Citation-graph construction from large ID lists | No (tight limits) |

| CORE | api-core.md ↗ | OA full-text downloads | Optional (recommended) |

| PubMed | api-pubmed.md ↗ | Biomedical search, PMC full text | No |

| Unpaywall | api-unpaywall.md ↗ | OA versions / PDFs | email (real) |

| Google Scholar | api-google-scholar.md ↗ | Broadest discipline coverage | No (needs stealth) |

| Europe PMC | api-europe-pmc.md ↗ | Biomed, PMID, full-text XML | No |

| NASA ADS | api-nasa-ads.md ↗ | Astrophysics, BibTeX export | Yes (free) |

| INSPIRE-HEP | api-inspire-hep.md ↗ | High-energy physics | No |

Pipeline workflows (6)

| Pipeline | File | Purpose |

|----------|------|---------|

| Paper discovery | pipeline-discovery.md ↗ | Keywords → candidate papers |

| PDF acquisition | pipeline-obtain-pdf.md ↗ | Metadata → full text (manual ladder) |

| Citation tracking | pipeline-citation-tracking.md ↗ | Forward/backward citation networks |

| Scholar analysis | pipeline-scholar-analysis.md ↗ | Impact, trends, h-index |

| LaTeX writing | pipeline-latex-writing.md ↗ | Compile, bibliography, figures, debug |

| Decision tree | decision-tree.md ↗ | "I have X — which API should I use?" |

Standalone references

Relationship to built-in web search

  • web-search-manual (returned by web_search(action="manual")) is the routing layer ("which tier to use for this URL?")
  • academic-research is the deep-dive layer ("how do I write OpenAlex filter parameters? what email does Unpaywall want?")
  • The two are complementary. If you're just scraping one publisher page and don't need the OA ladder, the built-in manual's scripts/extract_page.py is lighter.

Known caveats

  • Unpaywall's email parameter is required and must be real — placeholder addresses get HTTP 422. Set $LINGTAI_RESEARCH_EMAIL once.
  • CORE without an API key is harshly rate-limited (~100/day vs 10,000/day with a free key from https://core.ac.uk/services/api).
  • Semantic Scholar free tier is very tight (~100 req/day/IP, ~1 req/s practical). For large-corpus citation graphs use the batch endpoint — api-semantic-scholar-batch.md ↗. Request a key for any serious citation-network work.
  • Google Scholar requires a stealth browser (camoufox or playwright-stealth v2); legacy playwright_stealth API does not work.
  • arXiv enforces HTTPS — HTTP requests are 301-redirected automatically.
  • Library Genesis legality varies by jurisdiction — use is the user's responsibility. Pass --no-libgen to opt out.
  • Publisher-page extraction (Tier 5) — in-house stdlib+requests extractor (nothing to install; replaced the broken zhiping0913/Download_paper, issue #136). Fetches the already-accessible official landing page → structured Markdown. No paywall/CAPTCHA bypass, no cookie/credential handling — official pages only; login/paywall/unsupported-prefix/too-short is a clean miss. Heuristic (equations/figures may be lost). --no-publisher-extract to skip. Full contract: reference/publisher-page-extraction.md ↗.
  • Authorized-publisher tier (5b) — uses only access you already have: official DOI landing → same-host PDF, %PDF-+Content-Type validated. Never bypasses paywalls/CAPTCHAs, never reads/stores/replays cookies/credentials (cookies/auth never written to provenance). Most institutional access is IP-based, so a plain GET works on a licensed network and harmlessly misses off it. --no-institutional to disable. Full contract: reference/authorized-publisher-access.md ↗.
  • Zotero institutional full-text (Tier 6a) is a human-in-the-loop handoff, not an agent tool — for a batch where OA+5b both missed and the user runs Zotero Desktop on an institutional network: the agent stages rows via /connector/saveItems with a dated tag, the human clicks Find Full Text, the agent harvests PDFs back with provenance (copy-not-move, resolved_by: human Find Full Text). Never drive the UI via AppleScript/Accessibility (macOS TCC -1719/-1743, out of policy); no paywall bypass, no credential handling, no auto-LibGen. Full contract: reference/zotero-institutional-fulltext-handoff.md ↗.
  • Drafting citation-bearing academic writing without verifying sources first — under "fast"/"readable draft" pressure the model flattens DOI-verified papers, preprints, and search leads into one confident evidence layer, which reads as submission-ready and invites reviewer rejection. Pass the evidence-verification gate ↗ before drafting: verify a literature matrix first, keep A/B/C reliability tiers separate in the prose, and reduce scope (not verification) when speed is requested.
  • Writing an empirical paper iteratively can drift from the data — reviewer rounds make prose more polished and internally consistent without verifying it still matches the experiments on disk. Reviewer agreement is text-consistency evidence, not data-correspondence evidence. Anchor every claim to data files/runner code *before* writing, and re-derive (don't just rewrite) when feedback flags confusion. See reference/anti-pattern-text-consistency-vs-data-correspondence.md ↗.

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> Found a bug or issue? If you encounter any problems with this skill, load the lingtai-issue-report skill and follow its instructions to report it.

Frequently asked questions

What does the academic-research skill do?

Searches and downloads academic papers, analyzes citations, and writes LaTeX manuscripts.

How do I install academic-research?

Open the “Installation” block on this page and pick your agent — Claude Code, Codex, Cursor or Gemini CLI — for ready-made commands that copy the skill folder to the right place. Or copy the prompt from the “Via assistant” tab and let the assistant review and install the skill.

Which AI models work with academic-research?

Skills are plain Markdown instructions (the Agent Skills format), so academic-research works with any agent that reads SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and more. The model loads the instructions only when a task matches the skill's description.

Is academic-research free?

The skill is published openly by Lingtai-AI under the Apache-2.0 license. The skill itself costs nothing — you only pay your AI provider for the tokens you use.

Is it safe to install skills?

A skill is a set of instructions your agent will follow, so read SKILL.md and its companion files before installing. Scripts in the skill folder only run if your agent runs them — keep an eye on what it does and do not grant unnecessary permissions.

How is a skill different from an MCP server or a plugin?

An MCP server or plugin gives the model new tools — code that runs and returns a result. A skill gives it knowledge and process: how to approach a task, which steps to follow and what good output looks like. It needs no server or API key.

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