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 TashanGKD/tashan-cursor-skills --skill article-image-anglesgit clone --depth 1 https://github.com/TashanGKD/tashan-cursor-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/tashangkd/tashan-cursor-skills/article-image-angles)<a href="https://agentmods.dev/skills/tashangkd/tashan-cursor-skills/article-image-angles"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/article-image-angles/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/tashangkd/tashan-cursor-skills/article-image-angles"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/article-image-angles.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00063 | $0.00554 |
| Opus 5 | $0.00032 | $0.00277 |
| Sonnet 5 | $0.00013 | $0.00111 |
| Haiku 4.5 | $0.00006 | $0.00055 |
Grade A, and why
article-image-angles 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- article-image-angles — 100% identical, 0 lines differ
What it actually says
文章配图多视角分析(article-image-angles)
定位:wechat-article-writer Step 3(生成配图)的增强版。 核心价值:把「生成一张图」变成「从多种视角选最适合的图」,提高配图质量。
激活后立即执行
Step 1 读取文章标题和核心论点(从对话上下文获取) Step 2 分析可用配图角度(至少3种,最多5种): 常见角度类型: - 🔢 数据可视化角度:用图表/数字呈现文章核心数据 - 🎭 隐喻/类比角度:用视觉隐喻传达抽象概念 - 🔄 流程/机制角度:展示文章描述的系统/流程/循环 - ⚡ 对比/张力角度:突出文章的核心矛盾或转变 - 🌍 场景/情境角度:还原文章讨论的真实场景 Step 3 为每个角度写一段提示词(中文,适配 Qwen/GPT-4V 等图像生成模型) Step 4 向用户展示多个角度选项,等待选择 Step 5 用户确认后,用选定角度的提示词生成图片 Step 6 如有需要,根据反馈微调提示词重新生成
提示词格式规范
每个角度的提示词需包含:
- 构图描述(什么元素,如何排布)
- 风格描述(极简/插画/科技/水墨等)
- 颜色基调(与他山品牌色协调:蓝绿 rgb(111,167,170))
- 禁止元素(文字、人脸、版权图案)
变更记录
v1.0 — 2026-03-19 — 初始创建
根因:wechat-article-writer 配图只生成一张,缺少多视角分析和用户选择环节,配图质量依赖单次提示词质量。
验证状态:🔵 待验证
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.
- 10d ago First seen · 47 lines · 63 tokens per session scan A e409bf71eaed
article-image-angles is a skill published in the GitHub repository TashanGKD/tashan-cursor-skills (20 stars, last pushed 5mo ago), licensed MIT. It adds 63 tokens to every session and 554 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
cognitive-creative-synthesis
A brainstorming workflow that combines concepts from different areas of a knowledge system to suggest unusual approaches to a problem. DMN refers to the brain network associated with free association, while CEN refers to the network used to maintain goals and constraints.
android-feature
Workflow for implementing a new Android feature, screen, fragment, activity, dialog, adapter, or enhancement in this XML/MVVM template. Use whenever the user asks to add, build, implement, or extend functionality — before writing any code. Covers planning, the MVVM/MVI skeleton, the Android configuration checklist…
template-helpers
Catalog of the reusable building blocks shipped with this Android template — BaseActivity/BaseFragment, the helpers/ extension files (navigation, lifecycle, toast, snackbar, dialogs, images, permissions, theme, locale, settings intents, date, delay), common/ (Firebase, network, observers), and…
android-new-project
Workflow for turning a fresh copy of this Android template into a new app — renaming the package/namespace/applicationId, branding (icons, splash, palette, fonts), Firebase setup, signing config, stripping unused sample screens, and verifying the foundation. Use when the user says they are starting a new app…
android-preflight
Final verification checklist to run before declaring Android work finished — build, both themes, string resources, lifecycle and leak risks, registered permissions and components, resource parity between values and values-night, and honest reporting of what was and was not verified. Use at the end of any feature, fix…
android-ui-theming
Rules for Android XML layouts, Material 3 components, semantic color tokens, light/dark theming, dimensions (sdp/ssp), string resources and localization, accessibility, and edge-to-edge insets. Use when creating or editing any layout, drawable, style, color, vector, or string resource, or when a screen must work in…