Firecrawl Competitive Intel logo

Firecrawl Competitive Intel

Organization
firecrawl
firecrawl-competitive-intel

Monitor competitor pricing, features, changelogs, dashboards, and product changes with Firecrawl. Use for recurring competitive intelligence, pricing tier extraction, feature change tracking, or structured competitor alerts.

Overview

Publisherfirecrawl
Repositoryfirecrawl-workflows
Skill namefirecrawl-competitive-intel
Stars
175
Forks
38
Bundled files
Instructions only
LicenseISC
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 firecrawl on GitHub. Read the source before you install it.

Installation

Install the Firecrawl Competitive Intel 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/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-competitive-intel
  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/firecrawl/firecrawl-workflows.git /tmp/firecrawl-workflows
mkdir -p .claude/skills
cp -r /tmp/firecrawl-workflows/skills/firecrawl-competitive-intel .claude/skills/firecrawl-competitive-intel
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Firecrawl Competitive Intel 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 Firecrawl Competitive Intel 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 Firecrawl Competitive Intel 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.

Firecrawl Competitive Intel

Use this for monitoring competitors over time. This is not the broad competitor analysis workflow.

Onboarding Interview

Infer competitors, focus, cadence, and output format from context. If competitors are clear, proceed immediately.

Ask at most 1-3 concise questions only if blocked, such as the competitor list, focus area, or whether authenticated pages/profiles are required.

Firecrawl Collection Plan

For each competitor, use Firecrawl scrape or browser as needed:

  • pricing pages, annual/monthly toggles, expanded feature tables
  • feature and product pages
  • changelogs, blogs, release notes, docs updates
  • authenticated dashboards only when the user has legitimate access

Parallel Work

If appropriate, use sub-agents or equivalent parallel task runners. A natural split is one competitor per researcher or one focus area per researcher.

Each researcher should return pricing tiers, features, recent changes, source URLs, and confidence notes.

Final Deliverable

markdown
# Competitive Intel: [Competitors]

## Alerts
[Notable pricing, feature, or positioning changes]

## Per-Competitor Breakdown
[Pricing tiers, feature inventory, recent changes]

## Cross-Competitor Comparison
[Pricing table, feature matrix, key differentiators]

## Suggested Follow-Ups
[What to monitor next]

## Sources
[URLs visited]

## Rerun Inputs
workflow: firecrawl-competitive-intel
competitors: [list]
focus: [all/pricing/features/changelog]
cadence: [one-off/weekly/monthly]

JSON Shape

When structured output is requested, include generatedAt, competitors, pricing, recentChanges, features, and sources.

Quality Bar

  • Extract real plan names, limits, and dates when available.
  • Note contact-sales or gated details instead of guessing.
  • Preserve sources for diffing future runs.

Frequently asked questions

What does the Firecrawl Competitive Intel AI skill do?

Monitor competitor pricing, features, changelogs, dashboards, and product changes with Firecrawl. Use for recurring competitive intelligence, pricing tier extraction, feature change tracking, or structured competitor alerts.

Why use Firecrawl Competitive Intel on TypingMind?

Because you install it once and use it with any model. Firecrawl Competitive Intel 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 Firecrawl Competitive Intel in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-competitive-intel. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Firecrawl Competitive Intel?

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 Firecrawl Competitive Intel?

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

Is the Firecrawl Competitive Intel AI skill free?

Yes. It is published on GitHub by firecrawl under the ISC 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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