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 skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-denariogit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-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/skills/alterlab-ieu/alterlab-academic-skills/alterlab-denario)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-denario"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-denario/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.
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-denario"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-denario.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00144 | $0.01718 |
| Opus 5 | $0.00072 | $0.00859 |
| Sonnet 5 | $0.00029 | $0.00344 |
| Haiku 4.5 | $0.00014 | $0.00172 |
Grade A, and why
alterlab-denario 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Denario
Overview
Denario (by AstroPilot-AI) is a multiagent AI system designed to automate scientific research workflows from a described dataset through publication-ready manuscripts. It implements agents with AG2 and LangGraph, using cmbagent as the research-analysis backend, to handle hypothesis generation, methodology development, computational analysis, and paper writing.
Source: https://github.com/AstroPilot-AI/Denario | Docs: https://denario.readthedocs.io | Paper: arXiv:2510.26887 (v1.0, Nov 2025).
When to Use This Skill
Use this skill when:
- Analyzing datasets to generate novel research hypotheses
- Developing structured research methodologies
- Executing computational experiments and generating visualizations
- Conducting literature searches for research context
- Writing journal-formatted LaTeX papers from research results
- Automating the complete research pipeline from data to publication
Installation
Install with uv (recommended). Quote the extra so zsh does not glob [app]:
uv init
uv add "denario[app]"
The [app] extra pulls in the Streamlit GUI (DenarioApp); omit it for headless/library use. For Docker deployment or building from source, see references/installation.md.
LLM API Configuration
On init, Denario reads provider keys from the environment via its KeyManager (no config object). The relevant variables:
OPENAI_API_KEY— required (the analysis/results module needs it; OpenAI models are the cmbagent-mode defaults).GOOGLE_API_KEY— optional, a Gemini API key (the default LLM for the fastermode="fast"path). Note this is a plain Gemini key, not a Vertex AI service-account JSON.ANTHROPIC_API_KEY— optional (Claude).PERPLEXITY_API_KEY— optional, only for citation search.
Set them in the shell or a .env (loaded with python-dotenv before importing denario). Google Vertex AI is also supported as a backend; see references/llm_configuration.md for that and .env/Docker details.
What ships with it
5 files 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.
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.
- 7d ago First seen · 213 lines · 144 tokens per session scan A dbebdf633782
alterlab-denario is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 7d ago), licensed MIT. It adds 144 tokens to every session and 1,718 once invoked, about $0.0007 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 2026-09-05.
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