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Research Competitors Rival Pass

OrganizationPopular
gooseworks-ai
research-competitors-rival-pass

Step of the research-competitors playbook: the worker brief for profiling one rival at a capped depth, returning a fixed-shape profile. Run research-competitors instead; not for direct use.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill nameresearch-competitors-rival-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 Competitors Rival 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-competitors-rival-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-competitors-rival-pass .claude/skills/research-competitors-rival-pass
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Research Competitors Rival 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 Competitors Rival 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 Competitors Rival 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.

rival-pass — worker brief

You research one rival for one brand — or our own brand when the brief says so (then "openings" are our own events; skip "where we win"). The main run already chose the rivals and gave you the facts below.

Rules for this worker

  • Don't load any skill or playbook, and don't start subagents or workflows. This brief is all you need. If a dimension needs more method, read only that section of ../research-competitors/references/rival-craft.md.
  • Depth cap (standard run): about 12 web searches and 12 page fetches in total. Spend them by the company-type weighting below. A deep teardown (quarterly, or when asked) may double it. Stop a dimension when two reads add nothing new.
  • Never stop to ask. Public pages only: never log in, sign up, use fake details, or use unofficial mirrors (the Wayback Machine is fine). Never check or repeat a claim about our brand that no source gave you.
  • Every fact carries its link and date inline — the report quotes you directly. Say how sure you are in words ("confirmed", "likely", "a guess, because…").
  • A page that needs the browser (ad libraries, X, LinkedIn posts, script-only pages, review pages that block fetch) goes on Needs the browser with the exact URL or search — never "none found".

Inputs you get: rival name and site · our brand, what it sells, its approved claims · the frame we compete in · the typical-buyer scenario for pricing · company type · today's date · the rival's last saved snapshot, if any (report what changed since).

Get these, in this order

  1. News, last 90 days — 2–3 searches combining: shut down, acquired, raises, layoffs, pricing, launches, CEO. Anything in the last 30 days is a candidate opening, with the window it opens. Say exactly what happened: who bought what (company, or only assets and customers), who now serves the old customers, and on what offer.
  2. Launches, last 90 days — changelog or blog; the biggest one's demo, broken into hook · setup · reveal · proof · CTA, labelled from video, from transcript only or from page text only.
  3. Founder and exec posts — 1–2 people: site:linkedin.com/posts "<name>", site:x.com "<name>"; their repeated claims and teasers, linked — or "couldn't read (reason)".
  4. Ads — Meta, LinkedIn, Google, TikTok libraries, by the advertiser's name: what you could read (top ads, start date, days running, hook) or "couldn't open (reason)" / "Needs the browser". Never spend, return on ad spend or "best ad" as fact.
  5. Pricing — plans, price, the unit, free tier or trial, whether read on the vendor's page or third-hand; what a typical buyer like ours would pay a month (the scenario the brief gives you); which tier holds the features buyers care about; hidden costs.
  6. Positioning — the homepage headline word for word, who it's for, the lead claims.
  7. Buyers — at least one praise and one complaint, quoted verbatim with links, from more than one source where they exist (two review sites, or a review site plus Reddit or community); say which sites and how many you read. One site only (Trustpilot over-represents complaints) → say so. The praise is why their customers stay — never skip it.
  8. Hiring, customers and search — open roles by team (one look at the careers page); named customers, logos on the customers page a year ago that are gone now (Wayback, ../research-competitors/references/rival-craft.md §6 for the efficient way), job posts asking for "experience with "; who ranks or advertises on " alternative".

Weighting by company type

TypeSpend most onSpend least on (still check once)
B2B SaaSLinkedIn ads and posts, founder posts, reviews (G2/Capterra), pricing, launches, comparison searchesMeta, TikTok
DTC / ecommerceMeta and TikTok ads, creators, offers, Amazon/Trustpilot reviewshiring, LinkedIn
Consumer appapp-store reviews and rank, TikTok/Instagram ads, onboarding and paywallLinkedIn
Marketplace sellerlistings, price and coupon history, review themesfounder posts, hiring
Local businessGoogle Business reviews, local ads, offershiring, LinkedIn

Return this, in this shape (about 400–600 words)

markdown
## <Rival> — as of <date>
What they are: <one line> · Frame: <the category they claim>
News (90 days): <dated items with links> · Candidate openings: <event — date — window, or "none">
Launches: <dated> · Biggest launch breakdown (<from video | transcript only | page text only>): hook · setup · reveal · proof · CTA
Founder posts: <name, role — claims and teasers with links> or "couldn't read (reason)"
Ads: Meta <…> · LinkedIn <…> · Google <…> · TikTok <…> — each read (count and what it counts — "active now" or "shown since <date>" — top ads, start dates, days) or "couldn't open (reason)"
Pricing: <plans, price, unit, trial> — <vendor page | third-hand>, <link, date> · a typical buyer pays: <$/month for the scenario> · tier for key features: <…> · hidden costs: <…>
Headline (word for word): "<…>" · for whom · lead claims
Buyers say: praise "<quote>" (<site, link, date>) · complaint "<quote>" (<site, link, date>) · sites read and n per site · main review site: count and rating
Hiring: <roles by team> · Customers: <named, each confirmed / likely / a guess, linked> · likely lost: <logos gone since a year ago> · Search: <who ranks or advertises on "<rival> alternative">
Where we win / where we lose: <points, each with how sure>
Needs the browser: <exact URLs or searches>
Couldn't read: <source — why — what it would change>
Snapshot for next time: <active ads per library + ad ids and start dates, entry price and typical-buyer cost, headline, open roles, review site + count + rating, launches in 90 days — each with its last-read date>

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 Competitors Rival Pass AI skill do?

Step of the research-competitors playbook: the worker brief for profiling one rival at a capped depth, returning a fixed-shape profile. Run research-competitors instead; not for direct use.

Why use Research Competitors Rival Pass on TypingMind?

Because you install it once and use it with any model. Research Competitors Rival 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 Competitors Rival 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-competitors-rival-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 Competitors Rival 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 Competitors Rival Pass?

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

Is the Research Competitors Rival 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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