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.
npx agentmods add commands/lzy599775/agent-auto-sci-skills/ars-fullgit clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-skillsWrote 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.
[](https://agentmods.dev/commands/lzy599775/agent-auto-sci-skills/ars-full)<a href="https://agentmods.dev/commands/lzy599775/agent-auto-sci-skills/ars-full"><img src="https://agentmods.dev/badge/commands/lzy599775/agent-auto-sci-skills/ars-full.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00013 | $0.00115 |
| Opus 5 | $0.00006 | $0.00057 |
| Sonnet 5 | $0.00003 | $0.00023 |
| Haiku 4.5 | $0.00001 | $0.00012 |
Grade A, and why
ars-full 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 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.
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.
What it actually says
Trigger the academic-pipeline orchestrator ((pipeline) in MODE_REGISTRY.md — the orchestrator has no named mode of its own). Loads the skill and executes the complete academic research workflow (10-stage orchestration: deep-research → academic-paper → integrity → academic-paper-reviewer → revision → re-review → final integrity → finalize).
Mode reference: MODE_REGISTRY.md § academic-pipeline.
Skill entry: academic-pipeline/WORKFLOW.md.
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.
- 2d ago First seen · 9 lines · 13 tokens per session scan A 1feda0df1cd0
ars-full is a command published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 12d ago), licensed MIT. It adds 13 tokens to every session and 115 once invoked, about $0.0001 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 2026-09-03.
Other commands, from other repositories
ars-plan
ARS academic-paper plan mode — Socratic chapter-by-chapter planning.
memory-forget
Command "memory-forget" from waittim/MemoryCustodian, covering memory-forget and review the preview, then apply its plan id.
setup-code-intelligence
Check code-intelligence prerequisites (ripgrep + a language server) and print install hints.
ars-cache-invalidate
ARS /ars-cache-invalidate — drop cached verification entries for a citation key.
ars-abstract
ARS academic-paper abstract-only mode — bilingual abstract + keywords.
ab-test-design
You are a senior Data Science & AI/ML specialist. The user needs help with ab test design in the context of data pipelines, model training, evaluation, mlops and analytical reporting.