sciatlas-literature-review

sciatlas-literature-review is a skill for Codex from zjunlp/SciAtlas. It costs 101 tokens per session (1,510 once invoked), scanned A, original, MIT.

A guided workflow for finding and organizing research papers with SciAtlas, a paper-search service, and turning them into a survey outline or literature review. It covers setup through evidence-based writing for beginners.

In plain words
What is it for?
Use it to search a topic, map relevant papers, group them by methods or time periods, build an evidence pack, and draft or organize a literature review.
Why use it?
It removes the need to work out the research process, configuration, paper grouping, and evidence tracking by yourself. The workflow reads its saved results before producing the final review material.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to search a topic, map relevant papers, group them by methods or time periods, build an evidence pack, and draft or organize a literature review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zjunlp/sciatlas/sciatlas-literature-review
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zjunlp/SciAtlas --skill sciatlas-literature-review
Clone the repo
git clone --depth 1 https://github.com/zjunlp/SciAtlas

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for sciatlas-literature-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/zjunlp/sciatlas/sciatlas-literature-review/github.svg)](https://agentmods.dev/skills/zjunlp/sciatlas/sciatlas-literature-review)
Your own site
<a href="https://agentmods.dev/skills/zjunlp/sciatlas/sciatlas-literature-review"><img src="https://agentmods.dev/badge/skills/zjunlp/sciatlas/sciatlas-literature-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for sciatlas-literature-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/zjunlp/sciatlas/sciatlas-literature-review"><img src="https://agentmods.dev/badge/skills/zjunlp/sciatlas/sciatlas-literature-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 101 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,510 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 15
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00101 $0.01510
Opus 5 $0.00051 $0.00755
Sonnet 5 $0.00020 $0.00302
Haiku 4.5 $0.00010 $0.00151

Measured 12d ago against content hash d7d79aca9853, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

sciatlas-literature-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agent-skill/sciatlas-literature-review/SKILL.md · 143 lines

How it starts

The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SciAtlas Literature Review

Use this skill to run the repository literature-review workflow. The workflow performs topic profiling, SciAtlas backend paper search, evidence organization, method clustering, time slicing, outline planning, evidence-pack construction, and optionally full section drafting/integration.

Operating Contract

  • Run only sciatlas literature-review or python run_sciatlas.py literature-review for this skill.
  • Own the end-to-end novice flow: install or locate the CLI, guide registration, configure .env or shell variables, run the workflow, inspect artifacts, and synthesize the final review result.
  • Ask the user only for human-only values: missing topic/domain, email, verification code, SciAtlas token, LLM credentials that are not already configured, or one necessary scope clarification.
  • Do not ask the user to run shell commands when tool access is available.
  • Use --workflow flash by default for interactive work.
  • Use --workflow full when the user requests a comprehensive formal review or when flash artifacts are too thin.
  • Never disclose full API keys or tokens.
  • Read saved artifacts before answering.

Zero-Start Bootstrap

  1. Check whether the repository command works:
python run_sciatlas.py literature-review -h

If needed, fall back to sciatlas literature-review -h after installing the full checkout.

  1. This dedicated workflow requires a full SciAtlas checkout. If it is missing, clone the repository, change into it, then run python -m pip install -e ./sciatlas and python -m pip install -r requirements-workflows.txt. Do not use the GitHub #subdirectory=sciatlas package-only installation for this workflow.
  2. Check current environment and .env for SCIATLAS_API_KEY and LLM settings before asking the user.
  3. If no SciAtlas token is configured, guide the user to http://sciatlas.openkg.cn/register; ask for email, verification code, and returned sciatlas_xxx token only when needed.
  4. If LLM credentials are required and missing, ask only for the missing values. Use the user's provider values without printing them back.
  5. Configure the current shell or .env yourself, then run the workflow.

Read the full file on GitHub · 143 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 143 lines · 101 tokens per session scan A d7d79aca9853

Subscribe to this mod's changes

sciatlas-literature-review is a skill published in the GitHub repository zjunlp/SciAtlas (149 stars, last pushed today), licensed MIT. It adds 101 tokens to every session and 1,510 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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