Agent skill

Linkfox Aigc Textgen

by linkfox-ai in linkfox-ai/linkfox-skills

AI生文工具,使用大语言模型根据提示词生成文本内容,支持图/视频/文结合理解。模型可选GEM3FLASH(快速)和GEM31PRO(高质量复杂分析)。用户说"AI生文"、"AI写作"、"文本生成"、"帮我写一段"、"text generation"、"generate text"、"用AI写"、"AI分析图片内容"、"图片识别"、"视频分析"时触发。

MITAuto-check passed

Install Linkfox Aigc Textgen

skills CLI
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-aigc-textgen -a claude-code

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

GitHub CLI
$ gh skill install linkfox-ai/linkfox-skills linkfox-aigc-textgen --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/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/linkfox-aigc-textgen .claude/skills/linkfox-aigc-textgen && 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
linkfox-aigc-textgen
GitHub stars
107
Token cost
~1.5k tokens
SKILL.md length
344 words
Files
5 (incl. scripts, references)
Skills in repo
177
Repo updated
First seen
Licence
MIT

At a glance

AI生文工具,使用大语言模型根据提示词生成文本内容,支持图/视频/文结合理解。模型可选GEM3FLASH(快速)和GEM31PRO(高质量复杂分析)。用户说"AI生文"、"AI写作"、"文本生成"、"帮我写一段"、"text generation"、"generate text"、"用AI写"、"AI分析图片内容"、"图片识别"、"视频分析"时触发。

  • Works in 2 steps: 创建任务:POST /aigc/textGenAsync → 返回 taskId → 轮询查询:POST /aigc/textTaskQuery → 返回…
  • SKILL.md covers 核心特点, 模型说明, 思考等级 and 参数概览, plus 8 more sections
  • Runs Python scripts from its folder; calls python and jq; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY

What it does

Linkfox Aigc Textgen is an agent skill from linkfox-ai/linkfox-skills. AI生文工具,使用大语言模型根据提示词生成文本内容,支持图/视频/文结合理解。模型可选GEM3FLASH(快速)和GEM31PRO(高质量复杂分析)。用户说"AI生文"、"AI写作"、"文本生成"、"帮我写一段"、"text generation"、"generate text"、"用AI写"、"AI分析图片内容"、"图片识别"、"视频分析"时触发。

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/api.md`, `references/onboarding.md` and `scripts/aigc_textgen.py`).

It works with Python. The licence is MIT.

Example prompts

  • “text generation”
  • “generate text”
  • “AI分析图片内容”
  • “/linkfox-aigc-textgen”

Requirements

  • Python 3
  • A credential in LINKFOX_AGENT_API_KEY
  • A credential in LINKFOXAGENT_API_KEY

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. 创建任务:POST /aigc/textGenAsync → 返回 taskId
  2. 轮询查询:POST /aigc/textTaskQuery → 返回 PROCESSING / SUCCESS / FAILED

What it can do on your machine

Read from SKILL.md and the folder at commit 38fef04. 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

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • jq

    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 these keys or tokens, usually read from environment variables:

    • LINKFOX_AGENT_API_KEY
    • LINKFOXAGENT_API_KEY

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

Context cost

Linkfox Aigc Textgen loads about 1.5k tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 51 tokens; SKILL.md has 344 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.3k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 344 words, ~1,509 tokens.

Download SKILL.mdSave it as .claude/skills/linkfox-aigc-textgen/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
linkfox-aigc-textgen
description
AI生文工具,使用大语言模型根据提示词生成文本内容,支持图/视频/文结合理解。模型可选GEM_3_FLASH(快速)和GEM_3_1_PRO(高质量复杂分析)。用户说"AI生文"、"AI写作"、"文本生成"、"帮我写一段"、"text generation"、"generate text"、"用AI写"、"AI分析图片内容"、"图片识别"、"视频分析"时触发。

AI 生文

使用大语言模型根据提示词生成文本内容,支持传入图片, 视频等进行图文结合,视频文本理解和分析。

核心特点

  • 双模型选择:快速响应(GEM_3_FLASH)和高质量复杂分析(GEM_3_1_PRO)。
  • 图文/视频内容结合:imageUrls 同时支持图片与视频 URL;图片最多 10 张,视频通常传 1 个。
  • 思考深度可控:4 级 thinkingLevel 控制推理深度。
  • 异步两步调用:创建任务后立即返回 taskId,客户端轮询查询结果,避免长耗时同步超时。

模型说明

模型(model)说明适用场景
GEM_3_FLASH快速响应(默认)常规文案、简单分析、翻译
GEM_3_1_PRO高质量复杂分析深度分析、长文写作、复杂推理

思考等级

thinkingLevel说明
minimal接近无思考(GEM_3_1_PRO 不支持)
low低思考
medium平衡
high最大推理深度

参数概览

  • 必填字段:prompt、imageUrls(无图片且无视频时传空数组 [])、thinkingLevel(必须显式传入,建议默认 minimal)
  • 媒体 URL 约定:图片与视频 URL 均通过 imageUrls 传递(如视频分析传 ["https://example.com/ref.mp4"]);勿使用未文档化字段(如 videoUrl、videoUrls)

完整参数表、响应字段结构与错误码,见 references/api.md。

调用方式

采用异步两步模式(与 imagegen 一致):

  1. 创建任务:POST /aigc/textGenAsync → 返回 taskId
  2. 轮询查询:POST /aigc/textTaskQuery → 返回 PROCESSING / SUCCESS / FAILED
  • Python 脚本(内部已封装创建+轮询,传参方式不变):
    • python scripts/aigc_textgen.py --stdin — 推荐,从 stdin 读取 JSON 参数,避免 shell 转义问题(如 python scripts/aigc_textgen.py --stdin < params.json)
    • python scripts/aigc_textgen.py --stdin --content-only — 只输出 content 文本(同样已是单行)
    • python scripts/aigc_textgen.py '<JSON 参数>' [--inline] — 简单场景直传(prompt 含换行符时禁用)

轮询策略:单次 HTTP 超时 150 秒;轮询间隔从 10 秒起递减至 5 秒;总轮询时长最长 600 秒。完整参数/响应/错误码见 references/api.md。

换行符压平默认开启(无需任何 flag):所有输出模式下,content 的换行都会自动替换为单字符 ⏎(U+23CE),整段 content 变成单行;--content-only 只是改变"输出 content 文本 vs 完整 JSON",不影响该压平行为。

输出契约(其他 agent 按此解析)
  • stdout 只放机器数据,始终可 json.loads(--content-only 例外,其 stdout 是纯文本 content):
    • 默认(小结果)/ --inline:stdout = 完整响应 JSON
    • 大结果:stdout = JSON 信封 {"ok":bool, "truncated":true, "savedPath":"<路径>", "bytes":int, "content":"<单行文本>"}
  • 所有提示/摘要/诊断(CHAIN-HINT、Saved full response、summarize)一律走 stderr,不污染 stdout。
  • 退出码:成功 0;失败(网络错误 / errcode 非 200 / status==FAILED)非 0 —— agent 应优先用退出码判错。

读数据建议:小结果直接 json.loads(stdout) 取 content;大结果读 stdout 信封的 content(或按 savedPath 用 jq 抽完整字段),避免整份 JSON 进入上下文。

解决认证和算力问题

发生以下异常情况时,采用 references/onboarding.md 引导解决问题:

异常情况
  • 未配置API Key:环境变量未配置 LINKFOX_AGENT_API_KEY,也未配置 LINKFOXAGENT_API_KEY。
  • 响应401或402状态码
  • 响应提示算力或余额不足:消息含"算力余额不足/计费不足/余额不足/quota exceeded/insufficient balance/套餐到期/需充值/请充值",或类似含义的内容。

自动链式调用决策规则

Agent 必须遵循以下决策树,读到规则即自动执行,无需用户逐步指令。

用户需求后续是否涉及 作图 / 生图 / 换模特 / 视频 / imagegen / videogen?
│
├─ YES ──→ 使用 --content-only 模式(换行符已压平为单字符 ⏎,可安全内联拼接)
│           捕获 stdout → 内联拼进下游参数 JSON → 调用下游 Skill
│
└─ NO  ──→ 使用默认模式
            小结果 → json.loads(stdout) 取 content
            大结果 → 读 stdout JSON 信封的 content,或按 savedPath 用 jq 提取
换行符占位符约定(核心机制)

content 通常含真实换行符,直接进 shell 变量或拼接 JSON 会断行。脚本默认(任何模式,无需 flag) 把 content 的换行符统一替换为单字符 ⏎(U+23CE),同时覆盖真实换行控制符与字面量 \n 两种形态:

  • ⏎ 在 shell 单引号与 JSON 字符串中均无需转义,整段 content 变成单行,可被变量安全捕获、内联拼接;
  • 下游 AIGC 脚本(imagegen / videogen / videogen-multi)解析参数后会自动把 ⏎ 还原为换行符 (各 AIGC 脚本内联的 decode_nl_in_obj),因此文本无损传递;
  • 整段 content 变为单行后,可直接捕获进 shell 变量并内联拼接进下游参数 JSON,无需中间文件。
标准两步链式调用(imagegen / videogen / 任意 AIGC Skill)
bash
# ── Step 1:生文,--content-only 直接拿到单行 content(换行已是 ⏎),捕获进变量 ──────
PROMPT=$(python scripts/aigc_textgen.py --stdin --content-only < textgen_params.json)

# ── Step 2:内联拼接进下游参数并调用下游 Skill(jq 负责正确的 JSON 转义) ───────────
PARAMS=$(jq -nc --arg p "$PROMPT" \
  '{prompt:$p, imageUrls:["https://example.com/ref.jpg"], provider:"BANANA_PRO", outputNum:1, resolution:"1K", aspectRatio:"1:1"}')
python ../linkfox-aigc-imagegen/scripts/aigc_imagegen.py "$PARAMS"
# 下游脚本接收后自动把 ⏎ 还原为换行符

没有 jq 时,可直接把 $PROMPT 内联进单引号 JSON:因 ⏎ 无需转义且已无真实换行, 也能安全拼接(前提是 content 内不含双引号;含双引号时优先用 jq)。

各下游 Skill 的关键参数参考
下游 Skill关键字段(按需调整,prompt 由上游注入)
linkfox-aigc-imagegen{"imageUrls":[...],"provider":"BANANA_PRO","outputNum":1,"resolution":"1K","aspectRatio":"1:1"}
linkfox-aigc-videogen{"imageUrls":[...],"model":"WAN2_1","outputNum":1,"resolution":"720P","duration":5}
linkfox-aigc-imagegen-cloth{"imageUrls":[...],"outputNum":1,"aspectRatio":"1:1"}
linkfox-aigc-imagegen-product{"imageUrls":[...],"outputNum":1,"aspectRatio":"1:1"}

使用指引

  1. 模型选择:简单任务用 GEM_3_FLASH(默认,响应快);复杂分析、长文写作用 GEM_3_1_PRO。
  2. 提示词:最大 10 万字符,描述越具体效果越好。
  3. 图片/视频输入:通过 imageUrls 传入媒体 URL。纯文本用 [];图片理解传 1–10 张图;视频理解通常传 1 个视频 URL(如 .mp4)。复杂视频分镜/内容分析建议 GEM_3_1_PRO + thinkingLevel: low。
  4. 思考等级:需要快速响应选 minimal/low;需要深度推理选 high。
  5. 视频失败兜底:若返回视频不可读、媒体访问失败、10005 或内容为空,应抽帧为图片后再传入 imageUrls(参见下游业务 skill 的抽帧流程)。
示例

1. 基础文本生成

json
{"prompt": "Write a compelling product description for a wireless bluetooth speaker, highlighting portability and sound quality", "imageUrls": [], "thinkingLevel": "minimal"}

2. 图片 + 文本结合分析

json
{"prompt": "分析这张商品主图的构图和卖点表达", "imageUrls": ["https://example.com/product-main.jpg"], "model": "GEM_3_1_PRO", "thinkingLevel": "high"}

3. 视频 + 文本结合分析

json
{"prompt": "分析该参考视频的镜头节奏、卖点表达与可复刻的分镜结构", "imageUrls": ["https://example.com/reference.mp4"], "model": "GEM_3_1_PRO", "thinkingLevel": "low"}

4. 快速翻译

json
{"prompt": "Translate to German: 'Wireless Bluetooth Speaker with LED Light'", "imageUrls": [], "model": "GEM_3_FLASH", "thinkingLevel": "low"}

展示规则

  • 直接展示生成的文本内容。

限制

  • 提示词最大 10 万字符。
  • imageUrls 最多 10 个 URL;视频分析通常只传 1 个视频 URL,不建议与图片 URL 混传。
  • GEM_3_1_PRO 不支持 minimal 思考等级。
  • 失败时最多重试 3 次。

适用与不适用

适用:

  • 商品文案/标题/五点描述生成
  • 图片内容分析和描述
  • 文本翻译
  • 数据分析总结
  • 视频分析

不适用:

  • 图片生成 → linkfox-aigc-imagegen
  • 视频生成 → linkfox-aigc-videogen
  • 报告格式输出 → linkfox-report-generator

反馈

参见 references/api.md。

© linkfox-ai, MIT. 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 4 other files (scripts, references) in skills/linkfox-aigc-textgen of linkfox-ai/linkfox-skills.

  • SKILL.md
  • references/api.md
  • references/onboarding.md
  • scripts/aigc_textgen.py
  • scripts/onboarding.py

Open the folder on GitHubat commit 38fef04

Compare with similar skills

Linkfox Aigc Textgen 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.

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    按ASIN获取并分析亚马逊商品评论,支持15个站点(含美国站),按星级筛选评论。当用户提到亚马逊评论、美国站评论、商品评价、买家投诉、差评、好评、星级评分、评论分析、评论情感、产品改良建议、Vine评论、已验证购买评论、竞品评论研究、Amazon reviews, US reviews, Amazon.com reviews, product feedback, negative review…

    107 GitHub starsUsed in 1 repo~2.5k tokens
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Questions about Linkfox Aigc Textgen

What does Linkfox Aigc Textgen do?

AI生文工具,使用大语言模型根据提示词生成文本内容,支持图/视频/文结合理解。模型可选GEM3FLASH(快速)和GEM31PRO(高质量复杂分析)。用户说"AI生文"、"AI写作"、"文本生成"、"帮我写一段"、"text generation"、"generate text"、"用AI写"、"AI分析图片内容"、"图片识别"、"视频分析"时触发。. Linkfox Aigc Textgen is an agent skill from linkfox-ai/linkfox-skills.

How do I install Linkfox Aigc Textgen in Claude Code?

Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-aigc-textgen -a claude-code`. Or copy the skill folder (skills/linkfox-aigc-textgen in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-aigc-textgen in your project. Claude Code loads it when a task matches its description.

How do I install Linkfox Aigc Textgen in Codex?

Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-aigc-textgen -a codex`. Or copy the skill folder (skills/linkfox-aigc-textgen in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-aigc-textgen in your project. Codex loads it when a task matches its description.

Can I use Linkfox Aigc Textgen 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 linkfox-ai/linkfox-skills --skill linkfox-aigc-textgen -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkfox-aigc-textgen, .gemini/skills/linkfox-aigc-textgen, .github/skills/linkfox-aigc-textgen and .opencode/skills/linkfox-aigc-textgen in your project.

What does Linkfox Aigc Textgen need to run?

Going by SKILL.md and its folder, Linkfox Aigc Textgen needs Python for the scripts in its folder, the command-line tools its instructions call (python and jq) and credentials named LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY. Our summary lists: Python 3; A credential in LINKFOX_AGENT_API_KEY; A credential in LINKFOXAGENT_API_KEY.

Does Linkfox Aigc Textgen 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 Linkfox Aigc Textgen 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Linkfox Aigc Textgen use?

Linkfox Aigc Textgen is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Linkfox Aigc Textgen use?

About 1.5k tokens (SKILL.md is roughly 6k 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 1.8k tokens, read only when the agent opens those files.

What are the alternatives to Linkfox Aigc Textgen?

Skills that share tags, products or a category with Linkfox Aigc Textgen: MCP Server Builder (anthropics/skills, 180k stars), PDF Processing (anthropics/skills, 180k stars), NotebookLM Research Assistant (PleasePrompto/notebooklm-skill, 7.8k stars) and Manim Video Production (browser-use/video-use, 29k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linkfox Aigc Textgen?

linkfox-ai (a GitHub user) maintains it in linkfox-ai/linkfox-skills, which has 107 GitHub stars. The repository holds 177 skills in this directory. The repository was last updated on September 14, 2026.

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