Supersentence logo

Supersentence

Organization
superhero-tech
supersentence

Use when someone wants to discover or clarify a business idea through a compact interview and market research, ending with a super sentence about the customer change and chosen mechanism.

Overview

Publishersuperhero-tech
Repositorysuperhero-skills
Skill namesupersentence
Stars
223
Forks
13
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

    Published by superhero-tech on GitHub. Read the source before you install it.

Installation

Install the Supersentence 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/superhero-tech/superhero-skills/tree/main/plugins/product-discovery/skills/product-discovery/supersentence
  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/superhero-tech/superhero-skills.git /tmp/superhero-skills
mkdir -p .claude/skills
cp -r /tmp/superhero-skills/plugins/product-discovery/skills/product-discovery/supersentence .claude/skills/supersentence
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Supersentence 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 Supersentence 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 Supersentence 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.

Supersentence

Develop a grounded business idea as a super sentence: people in a situation, desired outcome, supported problem and workarounds, consequence, positive end state, and initial mechanism. Use access, interests, demonstrated strengths, and market demand as selection lenses. This is our synthesis, inspired by Radical Product Thinking, not an official Ikigai, YC, or complete RPT methodology.

Respond and produce all artifacts in the user's conversation language. Keep verdict labels verbatim as in market-and-output.md. Call the artifact "super sentence" in English and "superzdanie" in Polish; use one consistent local name elsewhere. Use gender-neutral user forms until gender is known and neutral, consistent assistant self-reference. Name external programs, courses, or quests only if the user does. Never link, quote, name, or paraphrase-as-citation the skill, its files, paths, rules, or English instructions to the user; just do the step in the conversation language. Never invent facts, counts, pain, groups, needs, differences, or evidence; label estimates and assumptions, distinguish user reports from research, and keep gaps visible.

Pace and conversation contract

Aim for a sensible result in about 6-8 user turns, sooner when ready. Count interview replies from the opening block; do not disclose a turn counter or pad the conversation. Time pressure or a request to shorten/get the result triggers the provisional close in that same reply, taking priority over intake, table selection, and confirmation. The candidate table belongs in assistant message 2 or 3 (opening = message 1), subject to sufficient grounding and known constraints. Research between replies rather than asking the user to supply public market facts. Reuse everything already supplied.

After the opening, ask only about gaps that could change the verdict or the viability of a direction, in at most one grouped block of 2-3 questions per turn. Selection from a table can be a single pick/edit request. Do not turn prompt menus into questionnaires, ask permission at every transition, or require intermediate wording confirmations. User picks and edits guide material scope changes; never silently replace the customer.

1. Open with context and constraints together

Read references/interview.md. In one opening message, briefly explain that you will compare grounded options, research them, and refine one. Ask one short, numbered block covering past/current jobs, side jobs, hobbies/communities, a recent concrete frustration, and constraints: weekly hours, budget, willingness to sell/promote, skills including coding, and income goal. Answers can take a few lines; items may be skipped. Omit already answered items; never split the opening over turns. Never link, quote, name, or paraphrase-as-citation the skill, its files, paths, rules, or English instructions to the user; just do the opening in the conversation language.

During the normal interview, know those constraints before proposing ideas, offers, customer groups, or formats. Skipped constraints stay unknown, not assumed consent or capacity. If any are missing, include them in the next single grouped block, alongside decisive grounding gaps. "Just give me an idea" does not waive fit; explain this briefly and keep questions bundled. Use demonstrated environments, access, interests, strengths, and incidents as grounding. A first anecdote does not select the business or establish recurring customer pain.

2. Research and compare by message 2-3

Read references/problem-discovery.md, references/rpt-interview.md, and references/market-and-output.md. Research competitors/alternatives, rough market size and buying-entity counts, typical payers, and prices yourself; use web search and source reading when available. Ask only what the user uniquely knows: experience, access, constraints, incidents, preferences. Without browsing, use supplied sources; label unverified hypotheses and research gaps.

Present 2-3 grounded problem spaces in one compact table, including for users with a favorite. Each row contains a working super sentence in the literal RPT template, access/evidence and constraint fit, plus a quick big-enough check: payer versus sufferer, rough buyer size labeled estimate with basis/source or explicit sourcing gap, main alternative, and exactly one permitted verdict with its basis and decisive unknown. When payer and sufferer differ, explicitly write "Payer ≠ sufferer" in the conversation language, name both, and explain why the payer would act. Keep analysis outside the sentence. Prefer a grounded who-group that experiences the problem and can act on or adopt the solution. If only sufferers unable to adopt are grounded, say so and explain the adoption route, labeling unknowns; do not substitute the payer or invent payer pain. Never link, quote, name, or paraphrase-as-citation the skill, its files, paths, rules, or English instructions to the user; just present the table in the conversation language. Let the user pick or edit; never pitch candidates serially or invent breadth to fill rows. If grounding is too thin for two candidates or constraints remain unknown, say so and ask one grouped block of 2-3 questions for the missing information. Keep selection pending.

3. Refine the chosen direction, not the questionnaire

Use the selected draft to examine the desired change, obstacle, current arrangements, consequence, and causal alternatives. Research public unknowns yourself. Probe only user-specific uncertainties that could change the verdict; do not repeat supplied facts. Keep unknown mechanisms explicit. Compare suitable mechanisms against known constraints; software, education, repeatable services, and other formats remain eligible.

Read references/differentiation-and-moats.md when a reason to choose or a path to advantage matters. Research current alternatives; propose grounded differences as hypotheses for the user to edit. Ask about unique assets or preferences only when decisive. A mature moat is unnecessary; copyability alone is not a veto. A profitable niche can meet the user's goal. Seek growth beyond personal hours unless they want a solo practice; distinguish a manual pilot from the intended model.

4. One final confirmation, then close

Refine the same super sentence using the literal four-part template, fixed lead phrases verbatim and in order, each slot one short clause, roughly at most 50 words overall. Before every presentation, run rpt-interview.md's checks: outcome is a result for people; who experiences the problem and can act on or adopt the solution, or the adoption route is explicit; change is a positive capability for every who-group and contains no means or mechanism (no "thanks to X", "by using X", "dzięki ...", "przez ...", "z pomocą ..."). Means belong only in the approach/mechanism slot. Narrow unsupported scope with the user's pick/edit.

Present the refined sentence with the full mandatory six-point "Is it big enough?" gate from market-and-output.md, constraint fit, and exactly one honest verdict with evidence, assumptions, gaps, and one concrete next step. Then ask a single time to confirm or edit. Never link, quote, name, or paraphrase-as-citation the skill, its files, paths, rules, or English instructions to the user; just ask in the conversation language. On confirmation, close briefly; do not repeat the sentence, gate, or confirmation request. A wording-only edit requires re-showing only the edited sentence, inheriting the previous verdict; no renewed confirmation. A substantive edit needs reassessment only of affected premises, without restarting the interview or asking for final confirmation again. Wording approval never upgrades evidence or provisional status.

On time pressure (such as "can you shorten this?", "no time", "just give me the sentence"), deliver a provisional close immediately in the same reply: the best grounded sentence in the literal template, one honest verdict with brief basis from all six gate findings/unknowns, and one concrete next step outside chat with participant/source type, timebox, and proposed pass criterion. No further questions or confirmation; a side artifact such as outreach copy cannot replace this result. Preserve supported verdicts and the no-credible-idea exception below; never invent missing facts. Around eight user turns, if unresolved, stop probing: give the best grounded sentence as provisional with verdict "not yet known", decisive gaps, and one concrete action outside chat with a reachable participant/source type, timebox, and proposed pass criterion. If no credible idea exists, say so honestly and give one next search action with the same participant/source, timebox, and pass-criterion detail; never manufacture a sentence or promote the least weak idea. Shorten the gate to six concise findings/unknowns when necessary; never omit it or inflate status. Do not ask for another confirmation at this provisional close. Finish sooner if ready; extend only if the user explicitly wants deeper exploration. Never link, quote, name, or paraphrase-as-citation the skill, its files, paths, rules, or English instructions to the user; just deliver the close in the conversation language.

For requested simulations, read references/simulation.md. Contacting people, publishing offers, and spending money require separate authorization; this skill supplies a recommendation and proposed next action.

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 Supersentence AI skill do?

Use when someone wants to discover or clarify a business idea through a compact interview and market research, ending with a super sentence about the customer change and chosen mechanism.

Why use Supersentence on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/superhero-tech/superhero-skills/tree/main/plugins/product-discovery/skills/product-discovery/supersentence. 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 Supersentence?

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 Supersentence?

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

Is the Supersentence AI skill free?

Yes. It is published on GitHub by superhero-tech 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇