Literature Review
neflibata-feng/MyArxiv-Agent
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.).
Screens records for systematic, scoping and rapid reviews against fixed eligibility rules, using two blinded AI reviewers and a third adjudicator, with traceable PRISMA counts.
Install Systematic Review Screener
$ npx skills add Imbad0202/academic-research-skills --skill sr-screener -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Imbad0202/academic-research-skills sr-screener --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Imbad0202/academic-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/sr-screener .claude/skills/sr-screener && rm -rf skills-srcUse ~/.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/
Install the "sr-screener" agent skill from https://github.com/Imbad0202/academic-research-skills/tree/main/sr-screener into .claude/skills/sr-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sr-screener", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Imbad0202/academic-research-skills/tree/main/sr-screenerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Imbad0202/academic-research-skills --skill sr-screener -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Imbad0202/academic-research-skills sr-screener --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Imbad0202/academic-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/sr-screener .agents/skills/sr-screener && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sr-screener" agent skill from https://github.com/Imbad0202/academic-research-skills/tree/main/sr-screener into .agents/skills/sr-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sr-screener", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Imbad0202/academic-research-skills --skill sr-screener -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Imbad0202/academic-research-skills sr-screener --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Imbad0202/academic-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/sr-screener .cursor/skills/sr-screener && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sr-screener" agent skill from https://github.com/Imbad0202/academic-research-skills/tree/main/sr-screener into .cursor/skills/sr-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sr-screener", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Imbad0202/academic-research-skills.git --path sr-screener--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Imbad0202/academic-research-skills --skill sr-screener -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Imbad0202/academic-research-skills sr-screener --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Imbad0202/academic-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/sr-screener .gemini/skills/sr-screener && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sr-screener" agent skill from https://github.com/Imbad0202/academic-research-skills/tree/main/sr-screener into .gemini/skills/sr-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sr-screener", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Imbad0202/academic-research-skills sr-screenerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Imbad0202/academic-research-skills --skill sr-screener -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Imbad0202/academic-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/sr-screener .github/skills/sr-screener && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sr-screener" agent skill from https://github.com/Imbad0202/academic-research-skills/tree/main/sr-screener into .github/skills/sr-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sr-screener", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Imbad0202/academic-research-skills --skill sr-screener -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Imbad0202/academic-research-skills sr-screener --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Imbad0202/academic-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/sr-screener .opencode/skills/sr-screener && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sr-screener" agent skill from https://github.com/Imbad0202/academic-research-skills/tree/main/sr-screener into .opencode/skills/sr-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sr-screener", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
sr-screener- GitHub stars
- 51k
- Token cost
- ~8.4k tokens
- SKILL.md length
- 3,852 words
- Files
- 27 (incl. scripts, references)
- Skills in repo
- 5
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Screens records for systematic, scoping and rapid reviews against fixed eligibility rules, using two blinded AI reviewers and a third adjudicator, with traceable PRISMA counts.
- Works in 3 steps: Explicit clear intent — user invokes a… → Cross-phase materials detected — user… → Ambiguous intent, no materials — user…
- Screening titles and abstracts against inclusion criteria for a systematic review
- SKILL.md covers Quick Start, Pasted and retrieved text is…, Trigger Conditions and Agent Team (4 Agents), plus 20 more sections
- Runs Python scripts from its folder; calls python
What it does
The skill turns a review proposal or PROSPERO protocol into confirmed eligibility rules before any record is read, then screens titles and abstracts and full texts. Every record gets two independent decisions from blinded AI reviewers, disagreements go to a third reviewer for adjudication, nothing is decided by default, and exclusions carry ordered codes. The AI reviewers support the team, and people sign off on the final screening.
It reads RIS, PubMed .nbib, Web of Science and CSV exports and removes duplicates. Outputs include PRISMA 2020 counts that trace back to files, RIS groups for EndNote or Zotero, an Excel log, a methods draft, and a literature_corpus handoff to the academic-paper skill. Quality control uses seed studies, near-miss rechecks and the kappa and PABAK agreement statistics, and batch runs can be resumed after an interruption.
Eight modes are available: protocol, quick, pilot, ta-screen, ft-screen, adjudicate, audit and report. The skill sits between deep-research, which handles the question, protocol and search, and academic-paper, which writes the review. Dual review at scale uses the Workflow tool or one Agent call per batch, while small sets work in one session. The deterministic steps are Python scripts that need Python 3.9 or newer and only the standard library, with openpyxl optional for the Excel log.
When your agent uses it
- Screening titles and abstracts against inclusion criteria for a systematic review
- Piloting the screening on a sample before the full run
- Resolving conflicts between two reviewers' decisions
- Auditing exclusions or producing the counts for a PRISMA flow diagram
Example prompts
- “Screen the records in search_results.ris against the eligibility criteria in protocol.md.”
- “Run a pilot screen on a sample of my exports before we commit to the full title and abstract pass.”
- “Adjudicate the screening conflicts and update the PRISMA counts.”
Requirements
- Python 3.9 or newer
- openpyxl, optional, for the Excel log
- Exported records in RIS, .nbib, Web of Science or CSV format
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Explicit clear intent — user invokes a specific skill via /ars-* slash command, or uses an unambiguous trigger keyword that maps to a…
- Cross-phase materials detected — user provides artifacts spanning ≥ 2 pipeline phases without naming a specific skill (e.g., pre-written…
- Ambiguous intent, no materials — user provides no artifacts and no clear request
What it can do on your machine
Read from SKILL.md and the folder at commit ebc21bf. 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 2 files in scripts/ (Python, from the files we listed), 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
Systematic Review Screener loads about 8.4k tokens when it runs, and up to ~19k if it reads all its reference files. Until then it costs about 257 tokens; SKILL.md has 3,852 words of instructions outside code blocks.
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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 3,852 words (~8,416 tokens).
“Screening is where a systematic review quietly loses studies: criteria drift, tired reviewers, records that fall between two batches. This skill makes each screening decision explicit and traceable. The criteria are fixed before any record is read, every record gets…”
- name
- sr-screener
- metadata.version
- 1.0.0
- metadata.last_updated
- 2026-09-29
- metadata.status
- active
- metadata.data_access_level
- raw
- metadata.task_type
- open-ended
- metadata.related_skills
- deep-research, academic-paper, academic-pipeline
Files
SKILL.md and 26 other files (scripts, references) in sr-screener of Imbad0202/academic-research-skills.
- SKILL.md
- agents/protocol_architect_agent.md
- agents/qc_auditor_agent.md
- agents/reporter_agent.md
- agents/screening_reviewer_agent.md
- examples/example_config_dta.json
- examples/example_protocol_dta.md
- examples/quick_screen_example.md
- references/decision_rules.md
- references/failure_paths.md
- references/orchestration.md
- references/protocol_template.md
- references/quality_control.md
- references/reporting_and_handoff.md
- references/reviewer_roles.md
- scripts/build_outputs.py
- scripts/build_workflow.py
- … and 10 more
Open the folder on GitHubat commit ebc21bf
Compare with similar skills
Systematic Review Screener next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Systematic Review Screener this skillImbad0202/academic-research-skills | 51k | — | ~8.4k | Automated safety check: Pass | Custom licence | |
| Literature Reviewneflibata-feng/MyArxiv-Agent | 126 | 20 repos | ~5.9k | Automated safety check: Notes | MIT | |
| NSFC Literature Review WriterHuiyuLi-2000/Chinese-Grant-Writer-Skills | 439 | 1 repos | ~1.4k | Automated safety check: Notes | MIT | |
| Social Science Paper Writingfakerqwq/social-science-paper-writing-skill | 382 | — | ~7k | Automated safety check: Pass | None | |
| Zotero Taxonomy Curatorganzoth/zotero-taxonomy-curator | 160 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Ieee SummarizeCloudWave818/ieee-skills | 359 | — | ~924 | Automated safety check: Pass | MIT |
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Social Science Paper Writing
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Zotero Taxonomy Curator
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Ieee Summarize
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Academic Search and Citation Router
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Academic Paper Reviewer
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Simulates a journal peer review of a manuscript with a five-seat reviewer panel, an editorial synthesizer and several review modes.
Academic Research Pipeline
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Orchestrates a ten-stage academic workflow from research to finished manuscript, including integrity checks, two rounds of peer review and revision.
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Related
Works with
Categories
Questions about Systematic Review Screener
What does Systematic Review Screener do?
Screens records for systematic, scoping and rapid reviews against fixed eligibility rules, using two blinded AI reviewers and a third adjudicator, with traceable PRISMA counts. The skill turns a review proposal or PROSPERO protocol into confirmed eligibility rules before any record is read, then screens titles and abstracts and full texts. Every record gets two independent decisions from blinded AI reviewers, disagreements go to a third reviewer for adjudication, nothing is decided by default, and exclusions carry ordered codes.
When should I use Systematic Review Screener?
Systematic Review Screener fits situations like: screening titles and abstracts against inclusion criteria for a systematic review; piloting the screening on a sample before the full run; resolving conflicts between two reviewers' decisions; auditing exclusions or producing the counts for a PRISMA flow diagram.
How do I install Systematic Review Screener in Claude Code?
Run `npx skills add Imbad0202/academic-research-skills --skill sr-screener -a claude-code`. Or copy the skill folder (sr-screener in Imbad0202/academic-research-skills) into .claude/skills/sr-screener in your project. Claude Code loads it when a task matches its description.
How do I install Systematic Review Screener in Codex?
Run `npx skills add Imbad0202/academic-research-skills --skill sr-screener -a codex`. Or copy the skill folder (sr-screener in Imbad0202/academic-research-skills) into .agents/skills/sr-screener in your project. Codex loads it when a task matches its description.
Can I use Systematic Review Screener 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 Imbad0202/academic-research-skills --skill sr-screener -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sr-screener, .gemini/skills/sr-screener, .github/skills/sr-screener and .opencode/skills/sr-screener in your project.
What does Systematic Review Screener need to run?
Going by SKILL.md and its folder, Systematic Review Screener needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.9 or newer; openpyxl, optional, for the Excel log; Exported records in RIS, .nbib, Web of Science or CSV format.
Does Systematic Review Screener 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 Systematic Review Screener 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 Systematic Review Screener use?
Systematic Review Screener has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Systematic Review Screener use?
About 8.4k tokens (SKILL.md is roughly 34k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 10k tokens, read only when the agent opens those files.
What are the alternatives to Systematic Review Screener?
Skills that share tags, products or a category with Systematic Review Screener: Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars), NSFC Literature Review Writer (HuiyuLi-2000/Chinese-Grant-Writer-Skills, 439 stars), Social Science Paper Writing (fakerqwq/social-science-paper-writing-skill, 382 stars) and Zotero Taxonomy Curator (ganzoth/zotero-taxonomy-curator, 160 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Systematic Review Screener?
Imbad0202 (a GitHub user) maintains it in Imbad0202/academic-research-skills, which has 51,242 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 10, 2026.
Source: Imbad0202/academic-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.