sciatlas-researcher-review

sciatlas-researcher-review is a skill for Codex from zjunlp/SciAtlas. It costs 74 tokens per session (992 once invoked), scanned A, original, MIT.

A research workflow that uses SciAtlas paper search to build an evidence-based profile of a researcher from their published work.

In plain words
What is it for?
It is for summarising a researcher's topics, representative papers, and contributions based on papers returned by SciAtlas.
Why use it?
It helps a newcomer set up the search, retrieve papers, inspect the results, and write a profile without treating the search output as a complete official résumé.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit It is for summarising a researcher's topics, representative papers, and contributions based on papers returned by SciAtlas.

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Install with agentmods
npx agentmods add skills/zjunlp/sciatlas/sciatlas-researcher-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-researcher-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-researcher-review

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/zjunlp/sciatlas/sciatlas-researcher-review"><img src="https://agentmods.dev/badge/skills/zjunlp/sciatlas/sciatlas-researcher-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 992 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 16
    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 $0.00074 $0.00992
Opus 5 $0.00037 $0.00496
Sonnet 5 $0.00015 $0.00198
Haiku 4.5 $0.00007 $0.00099

Measured 12d ago against content hash 1022d1324b77, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

sciatlas-researcher-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-researcher-review/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SciAtlas Researcher Review

Use this skill to create a researcher profile from search-papers evidence only. Because this skill does not call author-specific SciAtlas commands, treat the result as a literature-grounded profile, not an authoritative CV.

Operating Contract

  • Do not call any SciAtlas downstream, author, support, or report command. The only SciAtlas retrieval command allowed is search-papers.
  • Use only sciatlas search-papers for retrieval.
  • Own the end-to-end novice flow: install or locate the CLI, guide registration, configure environment variables, run retrieval, inspect artifacts, and write the researcher profile.
  • Ask the user only for email, verification code, token, or a clarification when the researcher name is ambiguous.
  • Do not ask the user to run shell commands when tool access is available.
  • Do not expose the full token.

Zero-Start Bootstrap

  1. Check whether the sciatlas executable exists without invoking a SciAtlas command: use Get-Command sciatlas -ErrorAction SilentlyContinue on Windows PowerShell or command -v sciatlas on macOS/Linux. Install if missing with python -m pip install -e ./sciatlas or python -m pip install "git+https://github.com/zjunlp/SciAtlas.git#subdirectory=sciatlas".
  2. If SCIATLAS_API_KEY is missing, guide the user through http://sciatlas.openkg.cn/register; ask for email/code/token only when needed.
  3. Configure:
$env:SCIATLAS_API_BASE_URL = "http://sciatlas.openkg.cn"
$env:SCIATLAS_API_KEY = "<token>"
setx SCIATLAS_API_BASE_URL "http://sciatlas.openkg.cn"
setx SCIATLAS_API_KEY "<token>"
export SCIATLAS_API_BASE_URL="http://sciatlas.openkg.cn"
export SCIATLAS_API_KEY="<token>"
  1. Verify with search-papers --top-k 1 only if needed.

Search Plan

Run only search-papers. Use the researcher name as part of the query and, when the user provides a field, include it as a keyword:

sciatlas search-papers --retrieval-mode hybrid --query "<researcher name> representative papers <field>" --keyword "high:<researcher name>" --keyword "middle:<field or known topic>" --top-k 10 --top-keywords 0 --max-titles 0 --max-refs 0 --bias-authorship high --bias-citation high --ranking-profile impact --report-max-items 10

Read the full file on GitHub · 86 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 · 86 lines · 74 tokens per session scan A 1022d1324b77

Subscribe to this mod's changes

sciatlas-researcher-review is a skill published in the GitHub repository zjunlp/SciAtlas (149 stars, last pushed 1mo ago), licensed MIT. It adds 74 tokens to every session and 992 once invoked, about $0.0004 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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