setup

An interactive setup guide for configuring optional API keys for Semantic Scholar, DeepXiv, and Review LLM.

In plain words
What is it for?
Use it to inspect and update the project's .env configuration for supported research and review services.
Why use it?
It shows which services are already configured and explains what each missing key is used for before changing the environment settings.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/skyllwt/autosci/setup
Any agent
npx skills add skyllwt/AutoSci --skill setup
Clone the repo
git clone --depth 1 https://github.com/skyllwt/AutoSci

Made for: Claude Code, Codex.

Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,384 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. Scan, not verified.
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 $0.00027 $0.02384
Opus 5 $0.00014 $0.01192
Sonnet 5 $0.00005 $0.00477
Haiku 4.5 $0.00003 $0.00238

Measured 2d ago against content hash daa9b2c14798, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

setup scanned grade B with 2 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 2d 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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

resp = requests.post('https://data.rag.ac.cn/api/register/sdk', json=payload, timeout=30)

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

resp = requests.post('https://data.rag.ac.cn/api/register/sdk', json=payload, timeout=30)
.claude/skills/setup/SKILL.md · 283 lines

How it starts

The opening of the file, as written. The whole thing — 283 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/setup

Guides you through ΩmegaWiki's optional API key configuration. Reads your current .env, shows what is and isn't configured, and helps you set up each key with clear explanations of what it does and how to get it. Safe to re-run at any time — only updates keys you choose to configure.

Inputs

  • No arguments required
  • Reads: .env (current configuration state)
  • Reads: config/setup-guide.md (reference for what each key does)

Outputs

  • Updated .env with any newly configured keys
  • A summary of current configuration status

Wiki Interaction

Reads

  • None (setup runs before any wiki exists)

Writes

  • None (does not touch the wiki)

Workflow

Step 1: Read Configuration Reference

Read config/setup-guide.md to load the complete reference for all configurable keys, including what each does, which skills use it, how to get it, and fallback behavior.

Step 2: Detect Current Environment

Run the following to check what is already configured:

python3 -c "
import sys, os
sys.path.insert(0, 'tools')
try:
    import _env
except Exception:
    pass
keys = {
    'SEMANTIC_SCHOLAR_API_KEY': 'Semantic Scholar',
    'DEEPXIV_TOKEN':            'DeepXiv',
    'LLM_API_KEY':              'Review LLM (API key)',
    'LLM_BASE_URL':             'Review LLM (base URL)',
    'LLM_MODEL':                'Review LLM (model)',
}
for k, label in keys.items():
    v = os.environ.get(k, '').strip()
    print(f'SET:{k}' if v else f'UNSET:{k}')
"

Also detect the Python environment and .venv status:

ls .venv/ 2>/dev/null && echo "venv:present" || echo "venv:absent"
python3 --version

Step 3: Show Configuration Status

Present a clear summary to the user, grouped by status:

ΩmegaWiki Configuration Status
================================
✓  ANTHROPIC_API_KEY      — managed by Claude Code (claude login)

Recommended:
✗  Semantic Scholar        — not set  (citation expansion 3x slower — get free key)

Optional:
✗  DeepXiv                 — not set  (semantic search unavailable)
✗  Review LLM              — not set  (cross-model review unavailable)

Read the full file on GitHub · 283 lines

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. 2d ago First seen · 283 lines · 27 tokens per session scan B daa9b2c14798

Subscribe to this mod's changes

setup is a skill published in the GitHub repository skyllwt/AutoSci (1,659 stars, last pushed 3d ago), licensed MIT. It adds 27 tokens to every session and 2,384 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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