content-production

content-production is a skill for Codex from tranfu-labs/tranfu-skills. It costs 163 tokens per session (3,830 once invoked), scanned A, original, MIT.

A Chinese-language content production workflow that turns a topic or Markdown outline into drafts and visual assets for five publishing platforms.

In plain words
What is it for?
Use it to create WeChat Official Account, Xiaohongshu, Zhihu, Weibo, and Toutiao content packages without publishing them.
Why use it?
It organizes research, evidence, variant writing, platform adaptation, image preparation, formatting, and quality checks in one repeatable process.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to create WeChat Official Account, Xiaohongshu, Zhihu, Weibo, and Toutiao content packages without publishing them.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tranfu-labs/tranfu-skills/content-production
Install

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.

Any agent
npx skills add tranfu-labs/tranfu-skills --skill content-production
Clone the repo
git clone --depth 1 https://github.com/tranfu-labs/tranfu-skills

Made for: Codex.

Wrote 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.

agentmods badge for content-production

README.md
[![agentmods](https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/content-production/github.svg)](https://agentmods.dev/skills/tranfu-labs/tranfu-skills/content-production)
Your own site
<a href="https://agentmods.dev/skills/tranfu-labs/tranfu-skills/content-production"><img src="https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/content-production/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.

agentmods 80×15 button for content-production

Your own site · 80×15
<a href="https://agentmods.dev/skills/tranfu-labs/tranfu-skills/content-production"><img src="https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/content-production.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 163 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,830 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00163 $0.03830
Opus 5 $0.00081 $0.01915
Sonnet 5 $0.00033 $0.00766
Haiku 4.5 $0.00016 $0.00383

Measured 11d ago against content hash 3a2782d99e01, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

content-production 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 11d ago.

The scan reads SKILL.md. This mod also ships 41 executable files (scripts/aggregate-titles.mjs, scripts/assemble-publish-packs.mjs, scripts/backend-lease.mjs, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

own-skills/content-production/SKILL.md · 177 lines

How it starts

The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Production

把本 Skill 当作唯一状态机和验收总控。具体能力由本地 provider Skill 执行;总控不重写 provider 的领域流程,也不允许 provider 创建第二套 run、门禁或用户确认。

完成定义

一次成功 run 必须交付:

  • 2 份平台中立母稿。
  • 5 个平台 x A/B = 10 份审校终稿。
  • 精确 34 个可兑现标题候选和 5 个自动或人工选择结果。
  • 5 套入选平台稿配图及优化记录。
  • 1 张标题准确、1923x818 的公众号 PNG 封面。
  • 1 份验证为零错误、零警告的公众号 clean HTML,以及浏览器预览。
  • qa.jsonqa.md 和人工发布交接单。

终点是本地交付包。禁止登录、创建平台草稿、排期、发布或读取发布后数据。

必读资源

开始新 run 或恢复旧 run 前完整读取:

  1. references/workflow.md:入口、阶段、自动决策和恢复顺序。
  2. references/capability-contracts.md:九个 provider 槽位与统一调用协议。
  3. references/artifact-contract.md:目录、schema、数量和最终验收。
  4. references/editorial-policy.md:事实、A/B、平台、标题和视觉边界。
  5. references/platform-profiles.json:五平台画像与数量配置。

核心规则

  • 只在 runs/<run-id>/ 写本次产物。provider 只能写总控授权的目录。
  • run.json、版本、门禁、失效和恢复点只由总控脚本维护。
  • 所有 provider 调用都使用 capability-contracts.md 的 request/result envelope;不要解析 provider 面向人的普通回复来拼装产物。
  • provider 未声明匹配的 content-production-provider:* marker,或契约检查失败时,停在初始化。
  • 事实与安全 > 平台规范 > 读者画像 > B 风格 > 表达偏好。
  • A/B 共享 claims、证据大纲、模型和参数。A 不读取 B 风格;B 只读取本次快照。
  • 十份平台稿必须从对应 A/B 母稿生成,不从公众号稿二次派生。
  • 标题只能读取审校稳定的十份终稿;内部数字评分不得成为总控接口。
  • 公众号封面是独立发布资产,不进入公众号正文图片发布映射 manifest.json
  • 07-visual/wechat-cover/cover.json 只记录生成、候选、视觉 QA 和源文件血缘;发布副本与压缩血缘由 package 阶段拥有。
  • illustration 先保存原生 manifest.md;所有正文图片优化后再由 package 阶段写发布映射 manifest.json。封面保持 PNG 和 1923x818
  • image compression provider 只写 staging candidate;总控仅在 candidate 严格更小时采用,否则逐字节保留原图,并由 package 独占发布扩展名、manifest 和 schema v2 optimization。
  • 图片写回五份入选 Markdown 后,最后执行公众号排版。
  • 整个 run 目录就是唯一交付包;核心阶段 Markdown、正文配图、公众号封面、HTML 和发布资产保留在各自原目录,不复制第二套汇总文件。
  • handoff.md 先列五个平台发布稿、图片目录、封面和 HTML,再按阶段索引 current Markdown、被采用的 prompts 与 native manifests;失败候选、旧 attempt、临时 checkpoint 和内部控制文件不进入运营索引。
  • 已批准或自动决定的文件禁止覆盖;修订写 .v002.v003 并失效下游。

入口与运行模式

接受且只接受一个创作入口:

  • --brief <一句话>:运行选题规划并自动选择主选题。
  • --topic <明确题目>:跳过候选发现,仍执行深度调研。
  • --outline <Markdown 路径>:快照大纲,仍执行事实核验和结构规范化。
  • --outline-text <粘贴的大纲>:与大纲文件入口相同。

默认 --run-mode autonomous。该模式保留 topicoutlinetitlesvisualfinal 五个审计门禁,但由总控根据固定规则写决策文件并立即批准,不暂停询问用户。只有用户明确要求逐阶段确认时才使用 --run-mode reviewed

Read the full file on GitHub · 177 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 11d ago First seen · 177 lines · 163 tokens per session scan A 3a2782d99e01

Subscribe to this mod's changes

content-production is a skill published in the GitHub repository tranfu-labs/tranfu-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 163 tokens to every session and 3,830 once invoked, about $0.0008 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 2026-08-31.

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