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Agent skill

Scite Database

by aipoch in aipoch/medical-research-skills

Access Scite.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its…

MITAuto-check passedResearch & Science

Install Scite Database

skills CLI
$ npx skills add aipoch/medical-research-skills --skill scite-database -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills scite-database --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Evidence Insight/scite-database' .claude/skills/scite-database && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
scite-database
GitHub stars
2k
Token cost
~1.4k tokens
SKILL.md length
633 words
Files
3 (incl. scripts)
Skills in repo
567
Repo updated
First seen
Licence
MIT

At a glance

Access Scite.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its…

  • Works in 5 steps: When to Use → Key Features → Dependencies → …
  • You need to evaluate a papers reliability
  • SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 6 more sections
  • Runs Python scripts from its folder; calls python

What it does

Scite Database is an agent skill from aipoch/medical-research-skills. Access Scite.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its acceptance in the literature.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scite-database_audit_result_v1.json` and `scripts/scite_client.py`).

It sits in Research & Science, covering Citation management. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • You need to evaluate a papers reliability
  • Its acceptance in the literature

Example prompts

  • “/scite-database”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. When to Use
  2. Key Features
  3. Dependencies
  4. Example Usage
  5. Implementation Details

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scite Database loads about 1.4k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 633 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 633 words, ~1,444 tokens.

Download SKILL.mdSave it as .claude/skills/scite-database/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
scite-database
description
Access Scite.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its acceptance in the literature.
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Scite Database Skill

This skill provides access to Scite.ai Smart Citations data. Given a paper DOI, it summarizes how the paper is cited by others—specifically whether citations are supporting, contrasting, or mentioning—to help you evaluate the strength and reception of scientific claims.

When to Use

  • Use this skill when you need access scite.ai smart citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its acceptance in the literature in a reproducible workflow.
  • Use this skill when a evidence insight task needs a packaged method instead of ad-hoc freeform output.
  • Use this skill when the user expects a concrete deliverable, validation step, or file-based result.
  • Use this skill when scripts/scite_client.py is the most direct path to complete the request.
  • Use this skill when you need the scite-database package behavior rather than a generic answer.

Key Features

  • Scope-focused workflow aligned to: Access Scite.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its acceptance in the literature.
  • Packaged executable path(s): scripts/scite_client.py plus 3 additional script(s).
  • Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

  • Python: 3.10+. Repository baseline for current packaged skills.
  • Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage

bash
cd "20260316/scientific-skills/Evidence Insight/scite-database"
python -m py_compile scripts/scite_client.py
python scripts/scite_client.py --help

Example run plan:

  1. Confirm the user input, output path, and any required config values.
  2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
  3. Run python scripts/scite_client.py with the validated inputs.
  4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

  • Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
  • Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
  • Primary implementation surface: scripts/scite_client.py with additional helper scripts under scripts/.
  • Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
  • Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Show full SKILL.md (269 more words)Show less

1. When to Use

Use this skill when you need to:

  1. Assess claim reliability: determine whether a paper is mostly supported or frequently contradicted by later work.
  2. Prioritize reading in a literature review: quickly gauge consensus and controversy around a key DOI.
  3. Fact-check scientific statements: validate whether a claim is broadly supported in subsequent citations.
  4. Compare competing papers: contrast citation sentiment profiles across multiple DOIs.
  5. Screen sources for downstream use: decide whether a paper is suitable to cite in reports, reviews, or product decisions.

2. Key Features

  • Citation classification counts: returns totals for supporting, contrasting, and mentioning citations for a given DOI.
  • Summary output formats: supports human-readable text output and machine-readable JSON output.
  • Basic venue/journal metadata (when available): returns limited publication/venue information if provided by the endpoint.

3. Dependencies

  • Python: 3.9+
  • requests: 2.x

4. Example Usage

Run from CLI (text output)
bash
python scripts/scite_client.py "10.1038/nature12345"

Example output:

text
--- Scite Analysis for 10.1038/nature12345 ---
Total Citations: 45
Supporting:      12
Contrasting:     1
Mentioning:      32
Run from CLI (JSON output)
bash
python scripts/scite_client.py "10.1038/nature12345" --format json

Example JSON (shape may vary by endpoint response):

json
{
  "doi": "10.1038/nature12345",
  "total_citations": 45,
  "supporting": 12,
  "contrasting": 1,
  "mentioning": 32
}

5. Implementation Details

  • Primary entry point: scripts/scite_client.py
  • Input: a single DOI string (e.g., 10.1038/nature12345)
  • Core logic:
    • Calls a public Scite endpoint for the DOI.
    • Parses the response to extract citation classification counts:
      • supporting
      • contrasting
      • mentioning
    • Computes/prints total_citations as the sum of the above (or uses the API-provided total when available).
  • Output modes:
    • Default: formatted text summary for quick inspection.
    • --format json: emits a JSON object suitable for pipelines and automated checks.
  • Limitations / notes:
    • Uses public Scite API endpoints; availability and response fields may change.
    • Citation snippets (context text) may require authentication and are not configured by default; this skill focuses on aggregate counts rather than full citation contexts.

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (scripts) in scientific-skills/Evidence Insight/scite-database of aipoch/medical-research-skills.

  • SKILL.md
  • scite-database_audit_result_v1.json
  • scripts/scite_client.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

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Citation Verification GuideGalaxy-Dawn/claude-scholar5.7k3 repos~1.9kAutomated safety check: PassMIT
Systematic Review ScreenerImbad0202/academic-research-skills51k—~8.4kAutomated safety check: PassCustom licence
Literature Reviewneflibata-feng/MyArxiv-Agent12621 repos~5.9kAutomated safety check: NotesMIT

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Categories

Questions about Scite Database

What does Scite Database do?

Access Scite.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its…. Scite Database is an agent skill from aipoch/medical-research-skills.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its acceptance in the literature.

When should I use Scite Database?

Scite Database fits situations like: you need to evaluate a papers reliability; its acceptance in the literature.

How do I install Scite Database in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill scite-database -a claude-code`. Or copy the skill folder (scientific-skills/Evidence Insight/scite-database in aipoch/medical-research-skills) into .claude/skills/scite-database in your project. Claude Code loads it when a task matches its description.

How do I install Scite Database in Codex?

Run `npx skills add aipoch/medical-research-skills --skill scite-database -a codex`. Or copy the skill folder (scientific-skills/Evidence Insight/scite-database in aipoch/medical-research-skills) into .agents/skills/scite-database in your project. Codex loads it when a task matches its description.

Can I use Scite Database in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill scite-database -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scite-database, .gemini/skills/scite-database, .github/skills/scite-database and .opencode/skills/scite-database in your project.

What does Scite Database need to run?

Going by SKILL.md and its folder, Scite Database needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Scite Database access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Scite Database safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Scite Database use?

Scite Database is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scite Database use?

About 1.4k tokens (SKILL.md is roughly 5.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Scite Database?

Skills that share tags, products or a category with Scite Database: Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars), Networkx (zLanqing/codex-claude-academic-skills, 4.6k stars), Citation Verification Guide (Galaxy-Dawn/claude-scholar, 5.7k stars) and Systematic Review Screener (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scite Database?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,974 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.