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Positioning

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matteotitta
positioning

Develops B2B SaaS positioning from your ICP, competitor and win-loss evidence. Maps what buyers compare you to, chooses between leading with a category or a problem, picks a primary and secondary anchor and up to three defensible differentiators, lays out 2 to 4 worked positioning options with a comparison canvas so you can decide, then locks the chosen one and tests it (clarity ladder, guarantee test). Triggers: "positioning", "how do we position", "what category are we in", "how do we differentiate from", "our homepage is confusing", "positioning options". Run before /messaging. Not for taglines or a messaging library (use /messaging).

Overview

Publishermatteotitta
Repositoryrepo-structure-in-house
Skill namepositioning
Stars
70
Forks
21
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Positioning 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/matteotitta/repo-structure-in-house/tree/main/.claude/skills/positioning
  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/matteotitta/repo-structure-in-house.git /tmp/repo-structure-in-house
mkdir -p .claude/skills
cp -r /tmp/repo-structure-in-house/.claude/skills/positioning .claude/skills/positioning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Positioning 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 Positioning 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 Positioning 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.

Positioning

Decide what you are, who it's for, what they'd use instead, and why you're the better choice, in words a buyer understands in five seconds. The method follows the public April Dunford school: start from the competitive alternatives buyers actually consider, and build out from there.

When to use it

  • The homepage doesn't explain what you do, or demos start with "so what is it exactly?".
  • You're choosing between going broad and niching down.
  • A new product, a new segment, or a competitor that moved.

Don't use it for taglines, value props or a full messaging library (/messaging, which runs after this), or for research you haven't done yet.

Inputs

Required: company name, a short description and the website URL.

Recommended: context/icp/, context/competitors/, context/win-loss/ and context/expert-pov/. Positioning without ICP and competitor evidence is opinion. If those are missing, say so, run what you can, and offer /icp-research and /competitor-research first.

Paths. Write to context/positioning/MMYY-positioning.md. Agency or consultant? Swap context/ for clients/<client>/context/ throughout.

Steps

  1. Read the current state. Fetch the homepage, pricing and about pages. Run the five-second test: do the headline and sub-headline say what it is and who it's for? Note the category, differentiation and ICP the site claims today.

  2. Map the alternatives. What would a buyer do if you didn't exist?

    • do it manually
    • keep a legacy tool
    • buy a direct competitor
    • stretch an adjacent tool
    • do nothing
    • build it with a general AI assistant

    Rank them by how often they show up in deals.

  3. Map the anchors. What could the positioning hang on?

    • an activity
    • a product category
    • a use case
    • a problem
    • a persona
    • a competitive alternative ("the X alternative for Y")

    Score the promising combinations on clarity, differentiation and relevance to the ICP.

  4. Make the binary choice. Category-led (buyers already know the category and you win inside it) or problem-led (the category is new, crowded or wrong, so you lead with the pain). Use an activity anchor only when no software category fits.

  5. Lay out the options. Take the top 2 to 4 combinations (3 by default) and work each one up:

    • primary and secondary anchor
    • a hero headline and sub-headline
    • the value in three parts: category, problem, differentiation
    • who it's for
    • the bet it makes
    • the risks

    Each option must change the anchor or the binary choice. No rewording of the same bet.

  6. Build the comparison canvas. One column per option, rows for clarity, differentiation, ICP relevance, proof available, competitive exposure and risk. Mark each cell's confidence: verified, inferred, estimated or unknown. Recommend one and name the trade-off each option forces. The user decides.

  7. Lock the chosen option. Up to three differentiators, each one a thing you'd guarantee with money on the line (pass, partial or fail). Name the primary competitive alternative and the market focus, with simple TAM maths (average deal size × customers needed).

  8. Run the clarity ladder. Compress the position to one word, one phrase, one sentence and one paragraph. If a level fails, go back to the anchors.

  9. Write the positioning statement in the form that fits the anchor:

    • Use case: "We help [persona] [do the job] without [friction], by [approach]."
    • Category: "We are a [category] that [differentiator], unlike [alternative] which [weakness]."
    • Alternative: "We're the [leader] alternative that [upgrade], for [persona] who [unmet need]."
    • Activity: "We help [persona] [do activity], replacing [manual process] with [mechanism]."
  10. Map the implications. What changes for messaging, for the ICP, and which channel leads with which facet (homepage: primary anchor; comparison pages: the alternative; case studies: proof that matches the anchor).

  11. Hand off to /messaging.

Output shape

Open with a TLDR (the one-sentence position) and one block of open decisions. Then: current state, alternatives, the options with the canvas, the committed position (anchors, differentiators with guarantee verdicts, statement, clarity ladder), implications, and sources. Each caveat is stated once.

What good looks like

  • A stranger reads the hero and knows what it is and who it's for in five seconds.
  • No more than three differentiators, each one provable.
  • The comparison set matches the buyer. Compare to other vendors only when buyers already use the category.
  • The options are real choices, not three phrasings of one idea.
  • The TAM maths is realistic, not hopeful.

Mistakes to avoid

  • "The platform for X" with nothing else.
  • "AI-powered" as the main differentiator.
  • Inventing a category nobody searches for.
  • Choosing the position before mapping the alternatives.
  • Differentiators you couldn't prove to a sceptical buyer.

Chain

Part of the free five-skill chain: /icp-research → /competitor-research → /tov-guidelines → positioning → /messaging. The other six context skills (company context, win-loss, founder POV, brand kit, funnel and goals) are in the paid context plugin ($19.99, link in the README).

Frequently asked questions

What does the Positioning AI skill do?

Develops B2B SaaS positioning from your ICP, competitor and win-loss evidence. Maps what buyers compare you to, chooses between leading with a category or a problem, picks a primary and secondary anchor and up to three defensible differentiators, lays out 2 to 4 worked positioning options with a comparison canvas so you can decide, then locks the chosen one and tests it (clarity ladder, guarantee test). Triggers: "positioning", "how do we position", "what category are we in", "how do we differentiate from", "our homepage is confusing", "positioning options". Run before /messaging. Not for t...

Why use Positioning on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/matteotitta/repo-structure-in-house/tree/main/.claude/skills/positioning. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Positioning?

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 Positioning?

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

Is the Positioning AI skill free?

Yes. It is published on GitHub by matteotitta 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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