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图像处理敏感数据clawhub未标认证来源可访问clear审计提醒

ai-image-skillsAI 图像技能

Agent Skill

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

总安装

5,090

周安装

210

GitHub Stars

1

下载量

1,663
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:ai-image-skills(AI 图像技能)
来源仓库:https://github.com/chuyun/ai-image-skills
安装命令:
openclaw skills install ai-image-skills
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install ai-image-skills

简介

用于辅助图像生成、图片编辑和视觉素材处理,支持文本生成图片及调用相关图像工具。

  • 适合让 Agent 根据描述生成图像、优化背景或整理提示词,提升视觉内容创作效率。
  • 通过 OpenAPI 规范构建并执行图像生成 REST 请求,适用于调试和记录图像调用流程。
  • 使用时需确认输入图片格式、版权来源及模型限制,确保输出符合预期和质量要求。
  • 涉及人物、品牌或商品素材时,应额外核对授权与内容合规性,避免侵权风险。

SKILL.md

name
ai-image-skills
description
Build and execute skills.video image generation REST requests from OpenAPI specs. Use when user needs to create, debug, or document image generation calls on open.skills.video.

ai-image-skills

Overview

Use this skill to turn OpenAPI definitions into working image-generation API calls for skills.video. Prefer deterministic extraction from openapi.json instead of guessing fields.

Workflow

  1. Check API key and bootstrap environment on first use.
  2. Identify the active spec.
  3. Select the SSE endpoint pair for an image model.
  4. Extract request schema and generate a payload template.
  5. Execute POST /generation/sse/... as default and keep the stream open.
  6. If SSE does not reach terminal completion, poll GET /generation/{id} to terminal status.
  7. Return only terminal result (COMPLETED/SUCCEEDED/FAILED/CANCELED), never IN_PROGRESS.
  8. Apply retry and failure handling.

0) Check API key (first run)

Run this check before any API call.

python scripts/ensure_api_key.py

If ok is false, tell the user to:

  • Open https://skills.video/dashboard/developer and log in
  • Click Create API Key
  • Export the key as SKILLS_VIDEO_API_KEY

Example:

export SKILLS_VIDEO_API_KEY="<YOUR_API_KEY>"

1) Identify the spec

Load the most specific OpenAPI first.

  • Prefer model-specific OpenAPI when available (for example /v1/openapi.json under a model namespace).
  • Fall back to platform-level openapi.json.
  • Use references/open-platform-api.md for base URL, auth, and async lifecycle.

2) Select an image endpoint

If docs.json exists, derive image endpoints from the Images navigation group. Use default_endpoints from the script output as the primary list (SSE first).

python scripts/inspect_openapi.py \
  --openapi /abs/path/to/openapi.json \
  --docs /abs/path/to/docs.json \
  --list-endpoints

When docs.json is unavailable, pass a known endpoint directly (for example /generation/sse/google/nano-banana-pro). Use references/image-model-endpoints.md as a snapshot list.

3) Extract schema and build payload

Inspect endpoint details and generate a request template from required/default fields.

python scripts/inspect_openapi.py \
  --openapi /abs/path/to/openapi.json \
  --endpoint /generation/sse/google/nano-banana-pro \
  --include-template

Use the returned request_template as the starting point. Do not add fields not defined by the endpoint schema. Use default_create_endpoint from output unless an explicit override is required.

4) Execute SSE request (default) with automatic fallback

Prefer the helper script. It creates via SSE and keeps streaming; if stream ends before terminal completion, it automatically switches to polling fallback.

python scripts/create_and_wait.py \
  --sse-endpoint /generation/sse/google/nano-banana-pro \
  --payload '{"prompt":"Minimal product photo of a matte black coffee grinder on white background"}' \
  --poll-timeout 900 \
  --poll-interval 3

Treat SSE as the default result channel. Do not finish the task on IN_QUEUE or IN_PROGRESS. Return only after terminal result.

5) Fall back to polling

Use polling only if SSE cannot be established, disconnects early, or does not reach a terminal state. Use GET /generation/{id} (or model-spec equivalent path if the OpenAPI uses /v1/...).

curl -X GET "https://open.skills.video/api/v1/generation/<GENERATION_ID>" \
  -H "Authorization: Bearer $SKILLS_VIDEO_API_KEY"

Stop polling on terminal states:

  • COMPLETED
  • FAILED
  • CANCELED

Recommended helper:

python scripts/wait_generation.py \
  --generation-id <GENERATION_ID> \
  --timeout 900 \
  --interval 3

Return to user only after helper emits event=terminal.

6) Handle errors and retries

Handle these response codes for create, SSE, and fallback poll operations:

  • 400: request format issue
  • 401: missing/invalid API key
  • 402: possible payment/credits issue in runtime
  • 404: endpoint or generation id not found
  • 422: schema validation failed

Classify non-2xx runtime errors with:

python scripts/handle_runtime_error.py \
  --status <HTTP_STATUS> \
  --body '<RAW_ERROR_BODY_JSON_OR_TEXT>'

If category is insufficient_credits, tell the user to recharge:

  • Open https://skills.video/dashboard and go to Billing/Credits
  • Recharge or purchase additional credits
  • Retry after recharge

Optional balance check:

curl -X GET "https://open.skills.video/api/v1/credits" \
  -H "Authorization: Bearer $SKILLS_VIDEO_API_KEY"

Apply retries only for transient conditions (network failure or temporary 5xx). Use bounded exponential backoff (for example 1s, 2s, 4s, max 16s, then fail). Do not retry unchanged payloads after 4xx validation errors.

Rate limits and timeouts

Treat rate limits and server-side timeout windows as unknown unless documented in the active OpenAPI or product docs. If unknown, explicitly note this in output and choose conservative client defaults.

Resources

  • scripts/ensure_api_key.py: validate SKILLS_VIDEO_API_KEY and show first-run setup guidance
  • scripts/handle_runtime_error.py: classify runtime errors and provide recharge guidance for insufficient credits
  • scripts/inspect_openapi.py: extract SSE/polling endpoint pair, contract, and payload template
  • scripts/create_and_wait.py: create via SSE and auto-fallback to polling when stream does not reach terminal status
  • scripts/wait_generation.py: poll generation status until terminal completion and return final response
  • references/open-platform-api.md: SSE-first lifecycle, fallback polling, retry baseline
  • references/image-model-endpoints.md: current image endpoint snapshot from docs.json

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

79.67%
按下载量换算1,325

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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