Lazyweb Explain Flow

Organization

LazywebHQ

lazyweb-explain-flow

EXPLAIN how something works with a hosted, tappable flow diagram — a walkthrough, a failure trace, an answer to "how does X work?", a hypothetical. Saves via lazyweb_explain_flow to insert-only storage, hosted at /explainer/<id>/. Trigger on: "explain this with a diagram", "walk me through how X works", "diagram why this failed", "show me how the pieces fit", "trace what happened".

Overview

Publisher	LazywebHQ
Repository	`lazyweb-skill`
Skill name	`lazyweb-explain-flow`
Stars	460
Forks	36
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by LazywebHQ on GitHub. Read the source before you install it.

Installation

Install the Lazyweb Explain Flow AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/LazywebHQ/lazyweb-skill/tree/main/skills/lazyweb-explain-flow
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/LazywebHQ/lazyweb-skill.git /tmp/lazyweb-skill
mkdir -p .claude/skills
cp -r /tmp/lazyweb-skill/skills/lazyweb-explain-flow .claude/skills/lazyweb-explain-flow

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lazyweb Explain Flow in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Lazyweb Explain Flow on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Lazyweb Explain Flow is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Lazyweb — Explain a Flow

Host an explanatory diagram: a sectioned flow-view page, stored insert-only — every call hosts a new standalone page that never collides with anything else.

MCP Setup

Use the hosted Lazyweb MCP tools at https://www.lazyweb.com/mcp.

Required tools:

lazyweb_health — verify connectivity when the MCP surface is uncertain
lazyweb_explain_flow — save the explanatory diagram (returns explainer_id + explainer_url)

If Lazyweb MCP is missing — or lazyweb_explain_flow isn't in the tool list — tell the user to run curl -fsSL https://www.lazyweb.com/install.sh | bash, reload, rerun.

MCP plan responses

Inspect every data-bearing tool result before applying its normal schema:

MCP_PRO_REQUIRED: relay the server message and returned intent-bound upgrade_url to the user, then stop. Do not retry another data tool or fall back to web/manual output.
FREE_REPORT_DAILY_LIMIT: relay the server message and returned intent-bound upgrade_url to the user, then stop. Do not retry another data tool or fall back to web/manual output.
Successful status: "locked_preview": relay display_to_user verbatim (or the returned MCP text if that is all the client exposes), including the preview and upgrade links. It is terminal: do not poll, retry another data tool, reconstruct output, or fall back.

Steps

Understand what needs explaining. A question ("how does search work?"), a failure ("why did this report ignore the intent?"), a walkthrough, a comparison. Ground it in the real code/logs — read the handlers, don't invent.
Build the explanatory diagram in the sectioned flow-view schema (sections, actors, nodes/edges with notes and real data payloads, bidirectional on round trips; an explanation earns its keep with REAL content, not boxes). Data snippets meet an exactness bar: actual payloads from the code/logs, … only to redact secrets (never to shorten content), and a sliced array keeps its first item(s) full-shape with the omission count in the note. Shape it for the QUESTION: order sections as the narrative, name the section titles as claims (e.g. "Where the run died — no model call"), put the "so what" in each node's note.
Save it: lazyweb_explain_flow({ title, summary, product?, diagram }) → share the returned explainer_url.

When NOT to use

Proposing changes the user should Accept/Decline → /lazyweb-propose-ui-changes.

Notes

Explainers are point-in-time and cheap — make as many as the conversation needs; they never collide with each other.

Frequently asked questions

What does the Lazyweb Explain Flow AI skill do?

Why use Lazyweb Explain Flow on TypingMind?

Because you install it once and use it with any model. Lazyweb Explain Flow is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Lazyweb Explain Flow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LazywebHQ/lazyweb-skill/tree/main/skills/lazyweb-explain-flow. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Lazyweb Explain Flow?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Lazyweb Explain Flow?

As many as you like. As long as a model supports skills, you can use Lazyweb Explain Flow with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lazyweb Explain Flow AI skill free?

Yes. It is published on GitHub by LazywebHQ under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Lazyweb — Explain a Flow

MCP Setup

MCP plan responses

Steps

When NOT to use

Notes

Frequently asked questions

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