← 返回 Skills 市场
antipas

Agent-first Marketing Image Generation

作者 Antipas · GitHub ↗ · v0.3.0 · MIT-0
cross-platform ⚠ suspicious
263
总下载
0
收藏
0
当前安装
4
版本数
在 OpenClaw 中安装
/install rynjer-image-generation
功能描述
Generates and refines image prompts, estimates costs, and produces business-ready images with predictable pricing for agent workflows via Rynjer API.
安全使用建议
This package implements the advertised image-generation flow and has a safe-looking mock mode, but there are important mismatches to review before enabling live mode: 1) The manifest declares no required env vars but the runtime/README require RYNJER_USE_LIVE, RYNJER_BASE_URL, and RYNJER_ACCESS_TOKEN for live operation — expect network calls to the default BASE_URL (https://rynjer.com) if you set live mode. 2) The IMPLEMENTATION.md describes an agent registration / owner-bind flow that issues a ryn_agent_v1_... key; understand and control who performs the owner bind so you don't inadvertently grant scopes. 3) Generation is paid: ensure any token you provide has minimal scopes and you understand pricing behavior (estimate vs generate). Recommendations before installing or running in live mode: - Start in mock mode (do not set RYNJER_USE_LIVE) to verify behavior locally. - If you enable live mode, only set RYNJER_ACCESS_TOKEN when you trust the Rynjer endpoint and have a token with minimal scopes. - Confirm the BASE_URL is the official service you expect; the code will use it directly. - Review the owner-bind/key creation process (out-of-band via UI) so you don't expose credentials to untrusted agents. - If you need stronger guarantees, ask the publisher to update registry metadata to declare the required env vars and clarify the exact auth steps and minimal scopes.
功能分析
Type: OpenClaw Skill Name: rynjer-image-generation Version: 0.3.0 The rynjer-image-generation skill provides a professional and well-documented interface for image generation workflows, including prompt optimization, cost estimation, and result polling. The core logic in `src/mock-runtime.js` is clean and follows standard practices, using Node.js HTTPS requests to communicate with a dedicated backend (rynjer.com) while managing credentials via environment variables. No evidence of data exfiltration, malicious execution, or prompt injection was found in the code or the instructional markdown files.
能力评估
Purpose & Capability
The skill's name/description (agent-first marketing image generation) matches the code and SKILL.md: prompt rewrite, cost estimate, generate, and poll are implemented. The runtime routes models and applies templates consistent with the marketing use cases. However, the package registry metadata declares no required env vars/credentials while the README/IMPLEMENTATION.md and runtime clearly support a live mode that needs RYNJER_USE_LIVE, RYNJER_BASE_URL and RYNJER_ACCESS_TOKEN (or an agent-created ryn_agent_v1_... key). That omission is an inconsistency to be aware of.
Instruction Scope
SKILL.md and code limit operations to prompt rewriting, local template lookup, cost estimation, generation requests, and polling the Rynjer API. The IMPLEMENTATION.md documents an agent registration/key-create flow (Ed25519 keypair generation and owner bind via UI) which is an auth onboarding step rather than hidden behavior; it may require out-of-band owner interaction. The instructions do not ask the agent to read unrelated host files or system secrets.
Install Mechanism
This is essentially an instruction-only skill with a small mock runtime JS file included. There is no install spec, no downloads, and nothing that writes executables or pulls remote archives — low install risk.
Credentials
The declared requirements list no environment variables or primary credential, but the runtime and documentation require (for live mode) RYNJER_USE_LIVE, RYNJER_BASE_URL, and RYNJER_ACCESS_TOKEN (or an agent-created API key). That mismatch is problematic because a user may install without realizing live-mode network calls will use an access token if provided. The number and type of env vars requested by the code (one bearer token and a base URL toggle) are proportionate to the purpose, but they should be declared up-front and the skill should clearly require minimal scopes for live usage.
Persistence & Privilege
The skill does not request always: true and does not modify other skills or system configs. It supports autonomous invocation by default (platform normal), which combined with live API access increases blast radius only if you enable RYNJER_ACCESS_TOKEN — a normal tradeoff for networked skills.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install rynjer-image-generation
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /rynjer-image-generation 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.3.0
Added 4 marketing templates (landing/ad/blog/ecommerce) and smart platform size recommendations. Updated positioning and documentation.
v0.2.0
Redesigned positioning: focused on short-path agent image generation for marketing use cases. Clear differentiation from full creative platforms.
v0.1.1
Tighten marketplace copy: clearer positioning, happy path, and live-verified credibility for soft launch
v0.1.0
Initial soft launch: agent-first image generation skill with prompt rewrite, cost estimate, live-verified auth flow, and polling support
元数据
Slug rynjer-image-generation
版本 0.3.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 4
常见问题

Agent-first Marketing Image Generation 是什么?

Generates and refines image prompts, estimates costs, and produces business-ready images with predictable pricing for agent workflows via Rynjer API. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 263 次。

如何安装 Agent-first Marketing Image Generation?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install rynjer-image-generation」即可一键安装,无需额外配置。

Agent-first Marketing Image Generation 是免费的吗?

是的,Agent-first Marketing Image Generation 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Agent-first Marketing Image Generation 支持哪些平台?

Agent-first Marketing Image Generation 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Agent-first Marketing Image Generation?

由 Antipas(@antipas)开发并维护,当前版本 v0.3.0。

💬 留言讨论