Competitor Research logo

Competitor Research

Community
matteotitta
competitor-research

Researches one B2B SaaS competitor across 13 dimensions (company, product, ICP, pricing, reviews, content, launches, search and AI visibility, tech stack, hiring, go-to-market, social, paid ads) and writes a sourced dossier with an executive summary, a threat level, strengths and weaknesses, and a data gaps section. Run it once per competitor, then compare. Triggers: "competitor analysis", "competitor research on", "what is [competitor] doing", "compare us to", "competitive landscape", "battlecard prep". Run after /company-context and /icp-research. Not for researching your own company (use /company-context).

Overview

Publishermatteotitta
Repositoryrepo-structure-in-house
Skill namecompetitor-research
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 Competitor Research 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/competitor-research
  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/competitor-research .claude/skills/competitor-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competitor Research 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 Competitor Research 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 Competitor Research 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.

Competitor research

Build a dossier on one competitor that a marketer, a seller and a founder can each act on. The rule that governs everything: no data point without a source. Every claim carries a URL and an access date, or it's marked [Not available].

When to use it

  • Building the context folder, after you know who your customer is.
  • Before positioning, so you know what buyers compare you to.
  • When a competitor shows up in deals more often, or launches something.

Don't use it for your own company (/company-context) or a single factual question ("what does X charge?"), which you can answer directly.

Inputs

Required: the competitor's name and website. If the name is ambiguous, confirm before you start.

Recommended: context/company/ and context/icp/ (so you can judge the threat against your own buyer), any existing dossier to refresh, and the questions the user cares about most (pricing, outbound, a feature).

Paths. Write to context/competitors/MMYY-<competitor-slug>.md. With two or more dossiers done, add context/competitors/MMYY-landscape.md. Agency or consultant? Swap context/ for clients/<client>/context/ throughout.

Tools. Web search and page fetching cover most of it. Exa helps find similar companies and clean page text; Firecrawl helps with pricing and comparison pages. Paid SEO and tech-stack tools are optional: if you don't have one, say so in that dimension rather than guessing. On a large site, list the pages first and only read the ones that matter (product, pricing, positioning, customers).

The 13 dimensions

  1. Company: founding, funding, headcount, leadership.
  2. Product: core offer, key features, what changed recently.
  3. ICP: who they sell to, judged from their case studies and logos.
  4. Pricing: model, tiers, entry price, what's gated behind sales.
  5. Reviews: themes in G2, Capterra or Trustpilot praise and complaints, with counts.
  6. Content: what they publish, how often, which topics.
  7. Launches: what they've shipped in the last 12 months.
  8. Search and AI visibility: the topics they rank or get cited for.
  9. Tech stack: tools visible on the site, if you can see them.
  10. Hiring: open roles by team, which signal where they're investing.
  11. Go-to-market: self-serve, sales-led or both; channels; partnerships.
  12. LinkedIn and social: founder and company activity, recurring themes.
  13. Paid advertising: ads visible in public ad libraries, angles they test.

Steps

  1. Confirm scope. Name, URL, and what the user wants to learn. Produces: a one-line brief.
  2. Research each dimension in the order above. Note the source and date for each finding. If a dimension needs a tool you don't have, write [Not available: needs X] and move on.
  3. Tag confidence. [VERIFIED], [INFERRED], [ESTIMATED], [UNAVAILABLE]. Aim for at least half verified.
  4. Assess strengths and weaknesses against your ICP, not in the abstract.
  5. Set a threat level: primary (same buyer, same problem, often in deals), enterprise tier (same problem, bigger buyer), direct ICP (same buyer, adjacent problem), watch (early or stealth), low, or defunct. Explain the call in two sentences.
  6. Write the executive summary last, in 2 to 3 short paragraphs.
  7. List data gaps with the action that would fill each one.
  8. If you have 2 or more dossiers, write a landscape file: threat table, feature comparison, where each competitor is weak, and 3 to 5 recommendations. Cite the dossiers rather than repeating them.
  9. Hand off to /positioning, which uses the competitor set as its list of alternatives.

Output shape

Title the file # Competitor research: [Name]. Then: a recent-changes line (on a refresh), executive summary, threat level, a section per dimension with inline (Source: X) notes, strengths and weaknesses, data gaps, and a sources table at the end with URL, access date and confidence per dimension.

What good looks like

  • All 13 dimensions present, each either filled or marked with why it's empty.
  • Major claims (funding, size, pricing) have more than one source.
  • Review themes come with counts, not adjectives.
  • The threat level would make sense to your sales team.
  • A refresh updates the existing file and notes what changed, rather than creating a duplicate.

Mistakes to avoid

  • Copying their marketing claims as fact. Note the claim, then the evidence.
  • Guessing pricing that's behind "contact sales".
  • Reporting old news as current. Date every finding.
  • A weakness list that's really a wish list ("their UX is bad") with no evidence.
  • Restating every dossier inside the landscape file.

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 Competitor Research AI skill do?

Researches one B2B SaaS competitor across 13 dimensions (company, product, ICP, pricing, reviews, content, launches, search and AI visibility, tech stack, hiring, go-to-market, social, paid ads) and writes a sourced dossier with an executive summary, a threat level, strengths and weaknesses, and a data gaps section. Run it once per competitor, then compare. Triggers: "competitor analysis", "competitor research on", "what is [competitor] doing", "compare us to", "competitive landscape", "battlecard prep". Run after /company-context and /icp-research. Not for researching your own company (use...

Why use Competitor Research on TypingMind?

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

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

Which AI models can use Competitor Research?

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 Competitor Research?

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

Is the Competitor Research 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.

View all

Set up your own AI workspace now

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