Agent skill

Report

by thun-res in thun-res/vlink

深度分析 VLink 的项目定位、技术成熟度、发展活跃度与行业前景,结合 报告当日的具身智能、自动驾驶、ROS 2、DDS/Zenoh/iceoryx 和边缘计算 背景,形成带来源的中文优势/劣势/机会/风险与路线建议。用户要求"前沿 检查报告"、"分析 VLink 前景"、"行业定位"、"活跃度分析"或"与 ROS2/ 自动驾驶/具身智能结合评估"时使用。

Apache-2.0Auto-check passed

Install Report

skills CLI
$ npx skills add thun-res/vlink --skill report -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install thun-res/vlink report --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/thun-res/vlink.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/report .claude/skills/report && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
report
GitHub stars
116
Token cost
~495 tokens
SKILL.md length
95 words
Files
6 (incl. references)
Skills in repo
16
Repo updated
First seen
Licence
Apache-2.0

At a glance

深度分析 VLink 的项目定位、技术成熟度、发展活跃度与行业前景,结合 报告当日的具身智能、自动驾驶、ROS 2、DDS/Zenoh/iceoryx 和边缘计算 背景,形成带来源的中文优势/劣势/机会/风险与路线建议。用户要求"前沿 检查报告"、"分析 VLink 前景"、"行业定位"、"活跃度分析"或"与 ROS2/ 自动驾驶/具身智能结合评估"时使用。

  • Works in 4 steps: 分册路由 → 执行流程 → 证据规则 → …
  • SKILL.md covers 1. 分册路由, 2. 执行流程, 3. 证据规则 and 4. 完成标准
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Report is an agent skill from thun-res/vlink. 深度分析 VLink 的项目定位、技术成熟度、发展活跃度与行业前景,结合 报告当日的具身智能、自动驾驶、ROS 2、DDS/Zenoh/iceoryx 和边缘计算 背景,形成带来源的中文优势/劣势/机会/风险与路线建议。用户要求"前沿 检查报告"、"分析 VLink 前景"、"行业定位"、"活跃度分析"或"与 ROS2/ 自动驾驶/具身智能结合评估"时使用。

Its SKILL.md is about 500 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `agents/openai.yaml`, `references/INDUSTRY-CONTEXT.md` and `references/LANDSCAPE.md`).

It works with GitHub. The repository describes itself as: VLink is a high-performance C++ communication middleware for autonomous driving and embodied intelligence, positioned as a full-scenario alternative to ROS 2. The licence is Apache-2.0.

Example prompts

  • “前沿 检查报告”
  • “分析 VLink 前景”
  • “与 ROS2/ 自动驾驶/具身智能结合评估”
  • “/report”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. 分册路由
  2. 执行流程
  3. 证据规则
  4. 完成标准

What it can do on your machine

Read from SKILL.md and the folder at commit 1793889. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Report loads about 495 tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 47 tokens; SKILL.md has 95 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~47
When it runs · the whole SKILL.md, loaded when a task matches
~495
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from thun-res/vlink at commit 1793889, republished under its Apache-2.0 licence (© thun-res). 95 words, ~495 tokens.

Download SKILL.mdSave it as .claude/skills/report/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
report
description
深度分析 VLink 的项目定位、技术成熟度、发展活跃度与行业前景,结合 报告当日的具身智能、自动驾驶、ROS 2、DDS/Zenoh/iceoryx 和边缘计算 背景,形成带来源的中文优势/劣势/机会/风险与路线建议。用户要求"前沿 检查报告"、"分析 VLink 前景"、"行业定位"、"活跃度分析"或"与 ROS2/ 自动驾驶/具身智能结合评估"时使用。

本 skill 输出证据驱动的中文战略技术报告,不修改项目代码。仓库事实以 本地源码、doc/、Git 历史和 GitHub 数据为准;行业现状具有时效性, 每次执行必须联网检索并标明资料日期和报告截止日。

1. 分册路由

只读取当前问题需要的分册;用户明确要求完整前沿报告时才依次读取全部:

范围读取
项目定位、成熟度或活跃度PROJECT-EVIDENCE.md
行业背景或单一领域趋势INDUSTRY-CONTEXT.md
生态定位、竞品或差异化PROJECT-EVIDENCE + INDUSTRY-CONTEXT + LANDSCAPE.md
完整前沿报告上述三册 + REPORT-TEMPLATE.md

2. 执行流程

  1. 记录报告日期、仓库 HEAD、分支、版本和分析范围。先读 AGENTS.md、 .agents/REPO-REFERENCE.md、.agents/FEATURE-INDEX.md,再按索引读取 相关 doc/ 和代码入口,不得只根据 README 下结论。
  2. 从 Git 与 GitHub 采集 30/90/365 天活动、release/tag、贡献者、Issue/ PR、CI 与文档事实。认证或 API 失败时明确缺口,不得用本地提交数冒充 全部社区活动。
  3. 联网检索报告当日的官方文档、标准、项目 release/roadmap、研究论文 和可信行业资料。技术能力比较优先使用一手来源;市场数字必须说明 发布机构、统计口径与年份。
  4. 按用户范围完成所需分析;只有完整报告才要求项目基线、行业需求、 生态位置、差异化、成熟度、优势劣势、机会风险与路线建议全部覆盖。 明确区分"源码证实"、"外部来源证实"与"分析推断"。
  5. 全量报告可按项目技术、社区活跃、行业背景、生态对比并行只读分析, 最后增加一轮对抗复核,专门寻找夸大、选择性指标、错误类比和缺失证据。
  6. 仅在用户明确要求落盘时,将结果写入 .agents/cache-report/report-vlink-<YYYYMMDD>.md;未要求落盘的 完整报告只在对话中给出,窄范围问题直接回答。除非用户另行要求, 不改源码、文档、Issue、PR 或 roadmap。

3. 证据规则

  • 所有会随时间变化的事实必须带访问日期和可点击来源;GitHub 活跃度给出 查询窗口,不只报累计值。
  • 相同项目的技术宣称优先引用其官方文档/源码/release,不引用搜索摘要。
  • stars、forks、下载量、提交数和作者数只是不同维度,不得单独等同采用度、 质量、社区健康或商业前景。
  • 没有公开证据时写"未找到可验证证据",不能把缺失推断为不存在。
  • VLink 与 ROS 2、Autoware/Apollo、Zenoh、DDS、iceoryx 等先判断竞争、 替代、集成或互补关系,再比较;不得把层级不同的项目硬排成同类。
  • 自动驾驶功能安全、实时性、量产部署、生态采用和性能优势均需专门 证据;仓库有相关代码不等于通过认证或已规模落地。
  • 建议必须能追溯到发现,写明价值、成本、依赖、风险和可验收结果,避免 空泛的"加强生态""完善文档""提升性能"。

4. 完成标准

完整报告的最终回复摘要当前定位、最重要的三项机会、三项风险和优先 建议,并给出报告路径。只有项目证据、行业证据、比较基线、活动指标、 反方检查和建议闭环全部完成后,才可称为完整前沿报告;窄范围问题只需 完成与请求直接相关的证据闭环。

© thun-res, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in .agents/skills/report of thun-res/vlink.

  • SKILL.md
  • agents/openai.yaml
  • references/INDUSTRY-CONTEXT.md
  • references/LANDSCAPE.md
  • references/PROJECT-EVIDENCE.md
  • references/REPORT-TEMPLATE.md

Open the folder on GitHubat commit 1793889

Compare with similar skills

Report next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Report compared with similar skills
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Diagnosing Superpowers Sessionsobra/superpowers297k3 repos~1.7kAutomated safety check: PassMIT
Greplooponyx-dot-app/onyx32k4 repos~3.3kAutomated safety check: PassMIT
GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Update V8 Versionopeninterpreter/openinterpreter69k2 repos~845Automated safety check: PassApache-2.0

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Works with

Questions about Report

What does Report do?

深度分析 VLink 的项目定位、技术成熟度、发展活跃度与行业前景,结合 报告当日的具身智能、自动驾驶、ROS 2、DDS/Zenoh/iceoryx 和边缘计算 背景,形成带来源的中文优势/劣势/机会/风险与路线建议。用户要求"前沿 检查报告"、"分析 VLink 前景"、"行业定位"、"活跃度分析"或"与 ROS2/ 自动驾驶/具身智能结合评估"时使用。. Report is an agent skill from thun-res/vlink.

How do I install Report in Claude Code?

Run `npx skills add thun-res/vlink --skill report -a claude-code`. Or copy the skill folder (.agents/skills/report in thun-res/vlink) into .claude/skills/report in your project. Claude Code loads it when a task matches its description.

How do I install Report in Codex?

Run `npx skills add thun-res/vlink --skill report -a codex`. Or copy the skill folder (.agents/skills/report in thun-res/vlink) into .agents/skills/report in your project. Codex loads it when a task matches its description.

Can I use Report in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add thun-res/vlink --skill report -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/report, .gemini/skills/report, .github/skills/report and .opencode/skills/report in your project.

What does Report need to run?

SKILL.md names no scripts, command-line tools or credentials: Report is instructions for the agent only.

Does Report access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Report safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Report use?

Report is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Report use?

About 495 tokens (SKILL.md is roughly 2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Report?

Skills that share tags, products or a category with Report: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Diagnosing Superpowers Sessions (obra/superpowers, 297k stars), Greploop (onyx-dot-app/onyx, 32k stars) and GitHub Deep Research (bytedance/deer-flow, 84k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Report?

thun-res (a GitHub user) maintains it in thun-res/vlink, which has 116 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on October 9, 2026.

Source: thun-res/vlink on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.