Ship a battlecard set for your sales team

Founders doing founder-led sales at 10-50 person startups, product marketing managers at companies too small to afford Klue or Crayon, and sales teams at early-stage B2B SaaS · Assemble in ~10 min; first battlecard draft in <20 min per competitor once installed.

ProductEdit flowon X● golden 94

step 1connector

Define scope and gather inputs

⚡ bring your own tool

step 2ready

Build structured profile for each competitor

competitor-profiling11 alts

step 3ready

Deep teardown — reviews, job postings, SEO, social

competitive-teardown

step 4ready

Generate the full battlecard set

competitive-battlecard-generator4 alts

step 5ready

Sharpen each card for live deals

competitive-battlecard

Did this recipe work for you?

What you get

▸One structured battlecard per competitor (3-8 cards) with strengths, weaknesses, pricing, positioning, and scripted talk tracks
▸Per-competitor teardown report covering review sentiment, job-posting signals, and SEO gaps
▸Deal-ready rebuttals and trap questions for each competitor named in active pipeline
▸Markdown or Notion-ready output the sales team can use in the field immediately

tools: No paid data sources required for public-signal pass; G2/Capterra API access optional (~$0 for manual review scrape via WebSearch)

tokens: ~$2-6 per competitor for the full 5-step run; ~$10-25 for a 5-competitor set

≈ $10-30/mo if refreshed monthly for a 5-8 competitor set

What stays yours

· Review each card for accuracy before distributing to the sales team — AI can hallucinate pricing or feature claims from stale web pages
· Add internal win/loss context the team holds in their heads (deal notes, verbal competitor FUD) that public signals cannot surface
· Decide which competitors warrant a card update when a product launch or pricing change is flagged

✓ Last verified 2026-06-11claude-sonnet-4-6 (subagent, test-mode fixtures)

✓ step 1 · Define scope and gather inputs

✓ step 2 · Build structured profile for each competitor

✓ step 3 · Deep teardown — reviews, job postings, SEO, social

✓ step 4 · Generate the full battlecard set

✓ step 5 · Sharpen each card for live deals

view sample outputs from this run

step 2 · Build structured profile for each competitor

# Competitor Profiles
_Skill: competitor-profiling | Inputs: competitor-shortlist.md, own-product-brief.md_

---

## 1. Linear (linear.app)

### Company snapshot
- Founded: 2019 | HQ: San Francisco, CA
- Funding: ~$52M Series B (2022, Sequoia)
- Employees: ~80 (est.)
- Revenue: not disclosed; est. $20–40M ARR based on funding and growth signals

### Messaging (as of mid-2026)
- Tagline: "The issue tracker built for high-performance teams"
- Hero claim: "Linear is the new standard for software project management — loved by engineering and product teams that move fast."
- Positioning: speed, bea…

step 3 · Deep teardown — reviews, job postings, SEO, social

# Teardown Intelligence
_Skill: competitive-teardown | Input: competitor-profiles.md_

---

## 1. Linear — Teardown

### G2 / Capterra review signals (synthesized from public review corpus)
**Avg rating:** 4.7 / 5 (G2, ~900 reviews)

**Top praise themes:**
- "Feels fast — native app performance in a browser"
- "Keyboard shortcuts make it feel like a superpower"
- "Beautiful design; my team actually wants to use it"
- "Best GitHub integration of any PM tool"

**Top complaint themes (weaknesses):**
- "No way to auto-capture action items from meetings or Slack — I still have to type everything in…

step 4 · Generate the full battlecard set

# Battlecard Set — Draft
_Skill: competitive-battlecard-generator | Inputs: teardown-intelligence.md, own-product-brief.md_

---

## BATTLECARD 1 — Linear vs. Clariva

### Quick snapshot
| | Linear | Clariva |
|--|--------|---------|
| Best for | Engineering teams wanting fast, beautiful ticket management | Engineering teams wanting sprint plans that build themselves from conversations |
| AI depth | Summarize + suggest (cosmetic AI) | Ingest + plan + alert (workflow AI) |
| Pricing | $8–16/seat/mo | $29–79/seat/mo |
| Setup time | Hours | 30 minutes (Slack + GitHub) |
| Meeting integration | …

The problem

When I need to arm my sales or product team with current competitive intelligence, I want an AI to scrape public sources (competitor websites, G2/Capterra reviews, changelogs, job postings) and output a structured battlecard per competitor with strengths, weaknesses, positioning, pricing, and talk tracks, so that my team stops losing deals to competitors they don't fully understand.

Cybernetic layers

Memorybyo

No harvested memory artifact tracks competitor changes over time. Store the final battlecard set in a shared doc (Notion / Google Drive) and re-run monthly to refresh. A file-diff layer comparing runs is a supply gap.

Backgroundgap

No scheduling layer exists in the library for this job. Competitor signals shift weekly; running a cron that re-triggers this recipe is the right posture but requires a custom wrapper (Claude Code background task or cron job) outside the skill set.

Harnessready

Claude Code is the runtime. Drop each ready skill into ~/.claude/skills/ and invoke by name. WebSearch must be enabled (default in Claude Code).

Click any step to see what fills it — and the ranked alternatives you can swap in.