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 tranfu-labs/tranfu-skills --skill format-contentgit clone --depth 1 https://github.com/tranfu-labs/tranfu-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/tranfu-labs/tranfu-skills/format-content)<a href="https://agentmods.dev/skills/tranfu-labs/tranfu-skills/format-content"><img src="https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/format-content/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/tranfu-labs/tranfu-skills/format-content"><img src="https://agentmods.dev/badge/skills/tranfu-labs/tranfu-skills/format-content.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 | $0.00109 | $0.02857 |
| Opus 5 | $0.00055 | $0.01429 |
| Sonnet 5 | $0.00022 | $0.00571 |
| Haiku 4.5 | $0.00011 | $0.00286 |
Grade A, and why
format-content 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Format Content
Convert one Markdown article into WeChat-compatible inline-styled HTML with the bundled red-and-white component library. Preserve the article's substantive content and produce only the two contracted files.
Orchestrated provider route
Before applying the standalone scope guard, inspect the task input for any of these provider markers:
contract: content-production-provider/v2capability: wechat_layoutprovider_contract: wechat-layout-v1content-production-provider: wechat-layout-v1
If any marker is present, do not use the standalone workflow or filenames. A complete packet must use
references/orchestrated-provider.md and
scripts/provider_contract.py. Partial, malformed, or conflicting provider markers return structured
BLOCKED; they never fall back to standalone output. Provider mode writes only its authorized staging
candidate and canonical result. The orchestrator owns promotion into the publish package and owns
layout-result.json.
Scope guard
- Trigger for requests such as “公众号排版”, “微信排版”, “把这篇 Markdown 排成公众号 HTML”, or “format this Markdown for a WeChat Official Account”.
- Accept either Markdown supplied directly in the request or one readable file whose extension is exactly
.md. - Do not accept
.doc,.docx,.pdf,.txt, HTML/rich text, or unstructured prose. Do not normalize those formats into Markdown; ask the user to provide Markdown instead. - Use only
<SKILL_ROOT>/references/theme-red-white.md. Do not select, recommend, create, or mix themes. - Do not rewrite or omit substantive content. Do not create a normal website, publish an article, create a WeChat draft, or call any WeChat API.
Guarded procedure
CREATE A TODO LIST FOR THE TASKS BELOW, with one TODO for each numbered stage, then execute stages 1–8 in order.
1. Establish paths and validate the input
Treat the installed directory containing this file as SKILL_ROOT and the Agent's current working directory as WORKDIR. Keep them separate: resolve bundled resources under SKILL_ROOT, and always write both outputs under WORKDIR, regardless of the source file's directory.
What ships with it
15 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.
- agents/openai.yaml 290 B
- assets/icon.png 321 B
- assets/icon.svg 359 B
- assets/preview-template.html 2.9 KB
- LICENSE 34 KB
- NOTICE 1.8 KB
- README.md 2.4 KB
- README.zh.md 2.1 KB
- references/common-components.md 11 KB
- references/orchestrated-provider.md 6.4 KB
- references/theme-red-white.md 28 KB
- scripts/component_lint.py 3.8 KB runs code
- scripts/provider_contract.py 36 KB runs code
- scripts/validate_gzh_html.py 9.7 KB runs code
- scripts/wrap_preview.py 1.8 KB runs code
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.
- 12d ago First seen · 184 lines · 109 tokens per session scan A 30b0892ee07b
format-content is a skill published in the GitHub repository tranfu-labs/tranfu-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 109 tokens to every session and 2,857 once invoked, about $0.0005 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…