
Why md2wechat Works Better as a Discovery-First Agent Workflow
md2wechat becomes much steadier when agents inspect the current capability surface first, then choose mode, modules, and resources before execution.
I increasingly avoid telling agents to “just start executing” with md2wechat.
This kind of tool has too many moving parts for guesswork to stay cheap.
Why this matters more here
md2wechat is not a single switch.
Even a normal workflow can involve choices like:
- what the current default mode is
- which providers exist right now
- which themes exist right now
- which prompt presets exist right now
- which advanced layout modules exist right now
If none of that has been confirmed, the workflow can drift from the first assumption.
The gains are practical
The biggest benefits are not abstract:
- fewer useless errors
- fewer bad assumptions
- rules that are easier to reuse across agents
- smoother upgrades when versions change
That is not process for its own sake. It is operational stability.
The order that works better
The steadier order looks like this.
First, inspect the current surface.
md2wechat capabilities --jsonSecond, list the resources relevant to the task.
md2wechat providers list --json
md2wechat themes list --json
md2wechat layout list --jsonThird, inspect the exact object you plan to use.
md2wechat providers show volcengine --json
md2wechat layout show hero --jsonOnly after that do you move to convert, preview, generate_image, or draft creation.
This also makes agent rules easier to write
There is another practical benefit.
You no longer need fuzzy rules built around guesses such as “if this probably exists.”
The rule can stay direct:
- list the current capability surface
- choose from what is currently exposed
- execute only after the choice is confirmed
That kind of rule survives much longer.
Closing thought
I increasingly think the best first move with md2wechat is not “convert now.”
It is “show me what this runtime can do first.”
Discovery first, execution second.
It looks like one extra step, but it usually removes more rework than it adds.
Continue with:
More Posts

How to Install and Use md2wechat-skill in OpenClaw
A complete OpenClaw guide for md2wechat-skill, covering the separate skill package, CLI runtime, ClawHub, validation, and the first successful task.

md2wechat-skill 2.0: From a Set of Commands to a Release-Ready WeChat Workflow
Why md2wechat-skill 2.0 is more than a small update, and what actually changed across the CLI contract, prompt catalog, image workflow, dual skill paths, installers, and documentation.

Title Generation for WeChat Articles: Hook Levels and Candidates
The title suggest handoff, the scoring formula, three hook levels, and how the final title lands in a draft.
Newsletter
Join the community
Subscribe to our newsletter for the latest news and updates