agentleFS
paulnugentukpaulnugentuk/pmmstack/skills/positioning-workshop/SKILL.md

positioning-workshop

Skill2 starsChanged 7 months agoNo licenceView on GitHub

A guided, multi-turn positioning workshop based on April Dunford's Obviously Awesome methodology. Walks the user through Dunford's five components in sequence — competitive alternatives, unique attributes, value themes, target customer, market category — with firm pushback on weak or lazy answers. Produces a structured positioning document with full reasoning chain at the end. Use this skill whenever the user mentions "positioning", "positioning workshop", "April Dunford", "Obviously Awesome", wants help defining their market category, wants to figure out their competitive alternatives, or says anything like "help me position my product", "who do we compete with", "what market are we in", or "I need to nail my positioning". Also trigger when the user is building a new product and needs to articulate what makes it different. This is an interactive workshop, not a one-shot analysis — it requires conversation.

8 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use company-intel.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • varunk130Skill

    company-intel

    Deep research on any company by scanning their public website to extract customers, partners, case studies, testimonials, key metrics, and competitive positioning. Produces a polished 1-slide PowerPoint summary. Use when: research a company, find customers, who are their customers, company research, company overview, customer list, company intel, customer logos, competitive research on company, scan website for customers.

    Also in 4 projects that use this

The file

Show its rules and text

We split this skill into the rules it gives an agent

41 rules. 0 are common, 41 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 8 edited versions we read keep these.

  • 41

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.