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Research Audience Segment Pass

OrganizationPopular
gooseworks-ai
research-audience-segment-pass

Step of the research-audience playbook: the worker brief for researching one buyer group, returning notes in a fixed shape. Run research-audience instead; not for direct use.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill nameresearch-audience-segment-pass
Stars
1.3K
Forks
219
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 gooseworks-ai on GitHub. Read the source before you install it.

Installation

Install the Research Audience Segment Pass 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/gooseworks-ai/goose-skills/tree/main/skills/marketing/research-audience-segment-pass
  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/gooseworks-ai/goose-skills.git /tmp/goose-skills
mkdir -p .claude/skills
cp -r /tmp/goose-skills/skills/marketing/research-audience-segment-pass .claude/skills/research-audience-segment-pass
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Research Audience Segment Pass 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 Research Audience Segment Pass 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 Research Audience Segment Pass 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.

segment-pass

You are researching one buyer group for one brand. This brief is complete: don't load any skill, don't read playbook files, don't start other agents; use only web search and page reads — no GooseWorks calls. Do every section below, inside the budget, then return. Never stop to ask. A blocked, empty or login-only source goes under "Couldn't read" — nothing you couldn't read may carry a conclusion or a move.

Inputs (in the prompt): the group and how to recognise one · the brand, what it sells, its price, its site, its approved claims · what the brand's own customer data says about this group, if shared · quote rows already saved for this group (add to them, don't re-mine) · the rivals · today's date.

Budget — stop at it

  • At most 12 web searches and 10 page reads. Search first; read a page only when you will quote or count from it. When a page read returns a summary, ask it for the exact sentences with author and date, not a summary.
  • Order if you run short: §2 problems and §3 words → §4 places → §5 moves → §1 wants → §0 size → §6 rivals. Say what you dropped.
  • Return at most 700 words in the shape at the end. No preamble.

Whose words count

Count: people in the group speaking first-hand — reviews (read on the review site), community threads and comments, their own posts — and the brand's customer data. Never as their voice: vendor blogs and landing pages (including a company writing about its own team), case studies, agency copy, trade press or analyst articles (a "brand rep" quoted by a journalist is second-hand), job posts, quotes copied onto someone else's page. Verbatim only, linked, dated, with who's speaking ("ops lead at a 40-person agency" — never a private person's name). At least 70% from the last 18 months; count it and report the share.

0. Size and buying roles

A count of buyers or companies, bottom-up (directory or store counts, company counts by size band, job-post counts, industry figures), each input linked or labelled an assumption, arithmetic in words. A community's member count is reach, not size. Who uses, who pays, who approves. No sourced count → "unknown".

1. What they want

1–3 outcomes in their words, linked — from their posts, review headlines, "how do I…" threads.

2. Their problems — and why they leave

The top 3–5, each: their words · how often (posts and distinct people) · how bad · one quote with link · solved / partly / not solved by the brand · proof (an approved claim, or "you'd need proof of X first"). Add why they switch or leave ("went back to X") where seen.

3. Their words

5+ quote rows for a group that may lead, 3+ otherwise — or "thin" and why. Each: "verbatim" — who — site, date, link. Add 2–3 rows of "they say / we say" (the brand's site words).

4. Where they gather

4–8 named places, each: activity (members, posts this week, cadence, next date) · evidence this group is there · link · read (you opened it and saw them) or unread.

5. Three moves

Each: channel · message in their words · first ask · who does it · what it needs · success check with a number and a date. Each rests on a read place; a move on an unread place is labelled "unverified — read the community and its rules first" and is never first.

6. Rivals

One line per rival: their words to this group, where they show up, where everyone sounds the same.

Return this shape

## <Group>
Recognise: … · Size: ~N (inputs + link + date, or unknown) · Uses / pays / approves: …
Evidence: N people first-hand, K kinds of source, M% last 18 months
Wants: …
Problems: | their words | how often | how bad | quote + link + date | solved/partly/not | proof |
Leave/switch: …
Words: "…" — who — (site, date, link) ×5 · they say / we say: …
Places: 1. <place> — activity — evidence they're there — read/unread — link + date seen …
Moves: 1. channel · message · ask · who · needs · check (number, date) — rests on <place> …
Rivals: …
Couldn't read / dropped: …

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 Research Audience Segment Pass AI skill do?

Step of the research-audience playbook: the worker brief for researching one buyer group, returning notes in a fixed shape. Run research-audience instead; not for direct use.

Why use Research Audience Segment Pass on TypingMind?

Because you install it once and use it with any model. Research Audience Segment Pass 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 Research Audience Segment Pass in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/marketing/research-audience-segment-pass. 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 Research Audience Segment Pass?

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 Research Audience Segment Pass?

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

Is the Research Audience Segment Pass AI skill free?

Yes. It is published on GitHub by gooseworks-ai 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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