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Using Humane

Community
glebis
using-humane

Route a design task to the right humane skill, and after any humane skill finishes, name the next one from the declared handoff graph instead of guessing. Reads the `handoffs:` / `accepts:` / `orchestrates:` keys in each skill's frontmatter, so the route is data, not recollection. Use at the start of design work when it is not obvious which skill owns the task, and at the end of any humane skill to find what it hands to. Not for non-design work. Triggers on where do I start, which humane skill, what comes next, what should I run after, humane cycle, design cycle order, "I finished the jtbd interview now what", "какой скилл дальше".

Overview

Publisherglebis
Repositoryhumane-agentic-design
Skill nameusing-humane
Stars
38
Forks
3
Bundled files
1
LicenseMIT
Links
  • 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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by glebis on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/glebis/humane-agentic-design/tree/main/humane/skills/using-humane
  4. 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.
2

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/glebis/humane-agentic-design.git /tmp/humane-agentic-design
mkdir -p .claude/skills
cp -r /tmp/humane-agentic-design/humane/skills/using-humane .claude/skills/using-humane
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Using Humane 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 Using Humane 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 Using Humane 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.

Using humane

Announce at start: "I'm using the humane:using-humane skill to route this to the skill that owns it."

Scope

This skill routes design work. It does not claim authority over unrelated tasks — a bug fix, a deploy, or a shell question has no humane owner, and routing one here is a false positive. If nothing below matches, say so and move on rather than stretching a design skill over a non-design task.

The two questions it answers

"Where do I start?" — match the intent to an entry point (table below).

"I just finished X, what now?" — do not recall the cycle from memory. Ask the graph:

bash
python3 scripts/graph.py --from layout-rules   # what it hands to, and when
python3 scripts/graph.py --to ux-writing       # who hands in here, and when
python3 scripts/graph.py                       # the whole graph
python3 scripts/graph.py --mermaid             # the graph as a diagram

The script reads the frontmatter of every skill in the plugin. It is stdlib-only and has no dependencies, so it runs anywhere the plugin is checked out.

Entry points

The user saysStart withNot with
"something's missing / nothing works / fresh machine"humane:setupanything else — it diagnoses first
"what should I build", "what are people hiring this for"humane:jtbda review skill; there is nothing to review yet
"mock this up", "show me the flow", "wireframe this"humane:prototypehumane:design-tokens — the structure is not settled yet
"implement this with Astryx", "fit this to our design system"humane:design-frameworkshumane:prototype — use the adapter after the product decision is settled enough to fit
"we need a brand / an identity"humane:brandkithumane:design-tokens — the tokens do not exist yet
"set up tokens", "compile to CSS", "check contrast"humane:design-tokenshumane:layout-rules, which only flags the pair
"pick a font", "does this font have Cyrillic"humane:type-specimenhumane:design-tokens, until a family is chosen
"generate on-brand images"humane:brand-illustratehumane:brandkit, which explores rather than produces
"what should this button say", "rewrite this error"humane:ux-writing—
"polish this text", "fix typography", "add nonbreaking spaces"humane:typographyhumane:ux-writing if the wording itself is still open
"add meaningful feedback", "design this micro-interaction", "make this state change satisfying"humane:semantic-micro-interactionshumane:sound-effects, which owns audio assets rather than the interaction meaning
"turn these ideas into a scroll story", "build a scrollytelling sequence"humane:narrative-scrollytellinghumane:semantic-micro-interactions, which owns bounded component feedback rather than narrative order
"generate UI sounds", "make a feedback sound palette"humane:sound-effectshumane:semantic-micro-interactions when the state-change meaning is still open
"how does this land", "test this tagline"humane:respondent-panelhumane:persona-review — strangers, not experts
"review this PRD as an engineer / investor"humane:persona-reviewhumane:respondent-panel — experts, not strangers
"review this UI", "check this dashboard"humane:layout-rules—
"usability audit", "heuristic evaluation"humane:nielsen-heuristics—
"can someone actually complete this", "test this flow"humane:walkthroughhumane:nielsen-heuristics — attempt, not inspect
"what's the transformation"humane:before-after—
"review this properly", "full review", "holistic audit"humane:reviewany single domain skill

When more than one row matches, humane:review wins — it is the one skill allowed to run several domains and consolidate them into a single verdict. When the user names a skill explicitly, their words win over this table.

What the graph keys mean

Three keys, three different relationships. Do not collapse them.

  • handoffs: — a peer route across an ownership boundary, with the when: that opens it. humane:layout-rules hands a contrast pair to humane:design-tokens because it does not own the fix.
  • accepts: — the receiving skill's acknowledgement of that route. Every handoff has one; the repo's test suite fails the build if it does not.
  • orchestrates: — a call, not a handoff. humane:review runs its domain skills and consolidates their findings. No reciprocity is owed, and the domain skills are unaware of it.

Cycles are legal and deliberate. humane:ux-writing and humane:respondent-panel route both ways: writing hands copy out for reactions, reactions hand the rewrite back.

Honesty guards

  • A handoff is a condition, not an instruction. Each edge carries a when:. If the condition did not occur, the cycle ends here — do not run the next skill for completeness. A humane:layout-rules pass that found no contrast issue does not hand to humane:design-tokens.
  • Ask before continuing. A handoff names what could come next. The user decides whether it runs.
  • The graph is not coverage. Following every edge is not a full review, and saying "I ran the cycle" is only true for the skills that actually ran. Name the ones that did not.
  • Never invent an edge. If scripts/graph.py shows no route, there is no route. Add one to the frontmatter — on both sides — rather than improvising it in conversation.

Claude Code extras: the skills are invoked as humane:<skill>. Announce each one as it starts, so a multi-skill cycle narrates itself.

In pi: there is no namespace prefix, so invoke a skill by its bare name — /skill:jtbd rather than /skill:humane:jtbd. Keep announcing each one as it starts. Install the whole package with pi install git:github.com/glebis/humane-agentic-design.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Using Humane AI skill do?

Route a design task to the right humane skill, and after any humane skill finishes, name the next one from the declared handoff graph instead of guessing. Reads the `handoffs:` / `accepts:` / `orchestrates:` keys in each skill's frontmatter, so the route is data, not recollection. Use at the start of design work when it is not obvious which skill owns the task, and at the end of any humane skill to find what it hands to. Not for non-design work. Triggers on where do I start, which humane skill, what comes next, what should I run after, humane cycle, design cycle order, "I finished the jtbd...

Why use Using Humane on TypingMind?

Because you install it once and use it with any model. Using Humane 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 Using Humane in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/glebis/humane-agentic-design/tree/main/humane/skills/using-humane. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Using Humane?

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 Using Humane?

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

Is the Using Humane AI skill free?

Yes. It is published on GitHub by glebis 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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