Competitor Intelligence Agent Skill

A ready to use Claude Agent Skill that researches a named competitor or the likely field for a bid and returns a structured profile or battlecard.

v1.0

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Available for

  • AutoRFP.ai
  • Claude
  • ChatGPT
  • Gemini
  • Grok
  • Copilot

Unlocked. Copy it into AutoRFP.ai or download it for your AI client. Select a client for its install steps.

What the skill does

  1. Structured competitor profile or battlecard for a specific bid

  2. Strengths, weaknesses, pricing, and positioning

  3. How that intelligence feeds win themes and evaluator trap setting

Skill source

The instructions behind every download

In the package

  • competitor-intelligence-agent-skill/
  • SKILL.md

SKILL.md

---
name: competitor-intelligence
description: Researches and builds structured competitive intelligence profiles
  for use in RFP responses, bid strategy, and sales positioning. Analyzes
  competitor products, pricing, strengths, weaknesses, and market positioning to
  help you differentiate. Use this skill when a user wants to research a
  competitor, build a competitive battlecard, understand a competitor's
  weaknesses for a bid, or needs competitive positioning for an RFP. Also
  trigger when users say "research [competitor name]", "competitive analysis",
  "battlecard", "how do we compare to [competitor]", "competitor weaknesses",
  "what does [competitor] do", or need to understand the competitive landscape
  for a specific deal. Works for both known competitors and for identifying
  likely competitors in a market.
---

# Competitor Intelligence for RFP & Sales

Researches competitors and produces structured intelligence profiles that directly inform RFP win strategy, bid positioning, and sales conversations. This is not generic market research -- it is tactical intelligence designed to help you win specific deals.

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Product demo

See it in AutoRFP.ai

Every draft carries a Trust Score for its sources and a Feedback Score for how fully it answers. Quality is measured by how little your team changes, and every approval records it. In a recent RFP, Red Rover had 95% of responses automated (83 out of 87 requirements). Measure it on your own RFPs in a two-week proof of concept.