# Kdense Scicomm Selected

> 精选 K-Dense Scientific Agent Skills 的科学交流工具包。用于 scientific-writing、peer-review、scientific-slides、scientific-schematics、citation-management、literature-review、markdown-mermaid-writing、research posters 等科研写作、审稿、引用、幻灯片、示意图和展示材料任务，并按 Auto-sci-research 的地理学加体育学论文路线进行封装。

- **Type:** Skill
- **Install:** `agentstack add skill-lzy599775-agent-auto-sci-skills-kdense-scicomm-selected`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Lzy599775](https://agentstack.voostack.com/s/lzy599775)
- **Installs:** 0
- **Category:** [Content & Media](https://agentstack.voostack.com/c/content-and-media)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Lzy599775](https://github.com/Lzy599775)
- **Source:** https://github.com/Lzy599775/agent-auto-sci-skills/tree/main/skills/kdense-scicomm-selected
- **Website:** https://lzy599775.github.io/agent-auto-sci-skills/

## Install

```sh
agentstack add skill-lzy599775-agent-auto-sci-skills-kdense-scicomm-selected
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# K-Dense Scientific Communication Selected

This wrapper packages selected Scientific Communication skills from `K-Dense-AI/scientific-agent-skills` for Auto-sci-research.

Use it when a task needs technical references for:

- scientific writing structure;
- peer-review thinking;
- citation management;
- literature review organization;
- slides, posters, schematics, or Mermaid diagrams.

## Local Adaptation

Use these upstream skills with local writing rules:

1. Preserve the manuscript's evidence strength and do not polish weak claims into stronger claims.
2. Build a claim-evidence map before rewriting important sections.
3. For sport geography and urban exposure papers, make public health, equity, mechanism, and policy relevance explicit.
4. For slides and posters, prioritize argument flow over decoration.
5. For citations, distinguish confirmed sources from candidate sources and never invent bibliographic details.

For domain-specific guidance, also read:

- `../agent-auto-sci-scicomm/references/k_dense_scicomm_mapping.md`
- `../agent-auto-sci-scicomm/references/manuscript_argument_checklist.md`

## Must Not Do

- Do not alter facts, values, methods, or citations during polishing.
- Do not hide uncertainty, limitations, or review risk.
- Do not use templates when the target journal requires a specific structure.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Lzy599775](https://github.com/Lzy599775)
- **Source:** [Lzy599775/agent-auto-sci-skills](https://github.com/Lzy599775/agent-auto-sci-skills)
- **License:** MIT
- **Homepage:** https://lzy599775.github.io/agent-auto-sci-skills/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-lzy599775-agent-auto-sci-skills-kdense-scicomm-selected
- Seller: https://agentstack.voostack.com/s/lzy599775
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.