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Agent Skill · 开发

tarsier(tarsier 命令行)

tarsier 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

tarsier 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 17,088。

总安装 442周安装 19GitHub Stars 13下载 155核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:tarsier(tarsier 命令行)
来源仓库:https://github.com/jpcaparas/skills
仓库路径:skills/tarsier
安装命令:
npx skills add https://github.com/jpcaparas/skills --skill tarsier
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jpcaparas/skills --skill tarsier

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合围绕仓库状态、代码变更或协作事项进行整理。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围、维护状态及是否会触发联网或命令执行。

支持 Codex、Claude、Cursor、Gemini CLI,通过 GitHub 安装。

来源仓库内路径:skills/tarsier

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jpcaparas/skills --skill tarsier;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

tarsier 怎么安装?

在终端执行 npx skills add https://github.com/jpcaparas/skills --skill tarsier。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

tarsier 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

tarsier 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

tarsier 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

tarsier 用的人多吗?

公开数据是累计安装 442 次,近一周安装 19 次,下载 155 次,GitHub 13 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

tarsier 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
tarsier

tarsier 命令行 · 本页

44213需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Tarsier

One-shot creative generator. Produces a complete SVG of a tarsier riding a bicycle, a rasterized 500×500 PNG with padding on white, and a markdown transcript recording what was made and how.

Invocation

/tarsier

No arguments. The prompt is static and never changes. Model name and reasoning level come from the harness when it exposes them.

What you produce

Three files in a new folder under the caller's current working directory:

{DIR}/
├── {BASE}.svg     # the raw SVG you authored
├── {BASE}.png     # 500x500 raster, 16px padding, white background
└── {BASE}.md      # transcript with metadata and the full SVG source

{BASE} follows the pattern tarsier-<model>-<reasoning>-<NZST-timestamp>.

Execution

Follow these steps in order. Each step has a verification cue — don't skip it.

Step 1 — Setup

  1. Model name: Read the current model ID from harness metadata. Strip any context-window suffix in brackets (e.g. claude-opus-4-6[1m] → claude-opus-4-6). When the harness does not expose a model ID, use unknown-model.
  2. Reasoning level: Read the active reasoning or effort level from harness metadata or the conversation. When unavailable, use default.
  3. Timestamp (NZST): TZ='Pacific/Auckland' date '+%Y%m%dT%H%M%S'
  4. Construct base name: tarsier-{model}-{reasoning}-{timestamp} — all lowercase, hyphen-separated.
  5. Create the output folder in the current working directory: mkdir -p./{BASE}

Step 2 — Generate the SVG

Respond to the prompt below as if it were the only instruction given. No embellishment, no negotiation, no asking the user for style guidance:

Generate an SVG of a tarsier riding a bicycle

Write your SVG to {DIR}/{BASE}.svg.

Technical requirements (for rasterization compatibility only — these do not constrain the art):

  • Complete <svg> element with xmlns="http://www.w3.org/2000/svg"
  • Include a viewBox attribute
  • No text or prose outside the SVG markup itself
  • Self-contained — no external image refs, no external font imports

A tarsier is a small nocturnal primate with huge round eyes, long fingers, a long tail, and a small furry body. Show it clearly on a bicycle. Beyond that, the art direction is up to you — detail level, style, and colour are intentionally unconstrained.

Step 3 — Rasterize to PNG

Run the rasterization script from this skill's scripts/ directory. The script wraps the SVG in a 500×500 white canvas with 16px padding so projectors and blog thumbnails render it consistently:

python3 <skill-dir>/scripts/rasterize.py "{DIR}/{BASE}.svg" "{DIR}/{BASE}.png"

<skill-dir> is the path where this skill was installed. If the harness does not expose it, resolve scripts/rasterize.py relative to the location of this SKILL.md file.

Verify the PNG was created and is non-empty:

test -s "{DIR}/{BASE}.png" && echo "PNG OK: $(wc -c < "{DIR}/{BASE}.png") bytes"

Step 4 — Write the transcript

Write {DIR}/{BASE}.md with this exact format (replace bracketed fields, keep the structure):

# Tarsier

| Field | Value |
|-------|-------|
| Date | {NZST datetime, e.g. 2026-04-10T14:30:45 NZST} |
| Model | {model} |
| Reasoning | {reasoning} |
| Prompt | Generate an SVG of a tarsier riding a bicycle |

## SVG Output

​```svg
{the complete SVG code — verbatim from Step 2}
​```

Step 5 — Report

Tell the user the output folder and list its contents. Example:

./{BASE}/
├── {BASE}.svg
├── {BASE}.png  (500x500)
└── {BASE}.md

Do not offer to upload, deploy, share, or host the output. Do not ask the user if they want another variant. The skill is one-shot by design.

The prompt

The prompt is always exactly:

Generate an SVG of a tarsier riding a bicycle

It is static. Do not paraphrase it in the transcript. Do not expand it with extra guidance inside your own reasoning. The value of a one-shot generator is that the input is fixed; the SVG is the only variable.

Naming convention

tarsier-<model>-<reasoning>-<NZST-timestamp>

  • Model: harness-reported model ID, lowercase with hyphens. unknown-model when unavailable. Strip context-window suffixes like [1m].
  • Reasoning: effort level for this session, lowercase (default, low, standard, high, thinking, etc.).
  • Timestamp: NZST in YYYYMMDDTHHmmSS format (no punctuation between date and time parts).

Example: tarsier-claude-opus-4-6-default-20260410T143045

Gotchas

1. rsvg-convert must be installed. The rasterization script shells out to rsvg-convert (from librsvg). On macOS: brew install librsvg. On Debian/Ubuntu: apt install librsvg2-bin. If the binary is missing the script will fail at Step 3 with a non-zero exit code — surface that error to the user instead of silently skipping the PNG.

2. SVGs without a viewBox will be cropped. The rasterizer extracts viewBox and falls back to width/height attributes. If neither exists it assumes 0 0 100 100, which almost always cuts off the drawing. Always include a viewBox — this is the single most common cause of a blank or clipped PNG.

3. Do not put anything outside the <svg> element. The rasterizer only copies content between <svg...> and </svg>. HTML comments, prose, or a DOCTYPE before the SVG tag will be silently discarded. Put comments inside the SVG with <!--... --> if you need them.

4. Timestamp must be NZST, not UTC or local. The TZ='Pacific/Auckland' prefix is intentional so outputs sort consistently across machines regardless of where the harness runs. Omitting it will produce inconsistent folder names across runs.

5. The prompt is frozen, the art is variable. The point of a one-shot generator is that the input never changes. Do not add creative guidance ("make it detailed", "use flat colours") to your own interpretation — the variance between runs is supposed to come from the model, not from you editorialising the prompt.

6. Output folder lives in the caller's CWD. mkdir -p./{BASE} creates the folder where the user invoked the command, not inside the skill directory. This is deliberate — users expect their files next to whatever they were working on.

Files in this skill

  • scripts/rasterize.py — SVG → 500×500 PNG wrapper. Executed in Step 3. Do not modify per-run.
  • evals/evals.json — test cases for the skill (smoke, edge, negative, disclosure).
  • templates/transcript.md — the transcript format from Step 4 as a ready-to-fill template.

平台分布

Codex

33.05%
按下载量换算51

Claude

30.15%
按下载量换算47

Cursor

20.92%
按下载量换算32

Gemini CLI

10.24%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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