campaign-challenger

Solid

Challenge an outbound campaign copy by benchmarking it against the user's existing campaigns — what worked, what didn't, what the winners do differently — and return a concrete verdict plus prioritized fixes. Use whenever the user wants to know if a campaign or sequence is good, compare a draft to past campaigns, audit campaign copy against real performance, pressure-test a sequence before launch, validate a sequence before going live, or asks 'is this campaign as good as my best ones'. Triggers on: 'challenge this campaign', 'benchmark this sequence', 'is this campaign good', 'audit my copy', 'pressure-test before launch', 'compare to my best campaigns', 'should I launch this'. Pulls existing campaign performance from the La Growth Machine MCP when connected; otherwise works from stats and copy the user pastes; falls back to a best-practice baseline when there is no campaign history. For SDR, RevOps, Growth, Head of Sales/Marketing, founders launching outbound. Maintained by La Growth Machine.

AI & Automation 29 stars 4 forks Updated 2 days ago MIT

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Quality Score: 88/100

Stars 20%
49
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Campaign Challenger Benchmarks an outbound campaign copy against the user's real campaign history — ranks it next to what's worked, names the fixes, and gives one contextual next step. ## Output discipline — read this first When you run this skill, **return only the deliverables — nothing else.** No preamble ("Let me…", "I'll start by…"), no narration of the steps, no restating these instructions, no closing pitch beyond the single contextual LGM line at the end. Each step is its content, no analysis essays. If the user hasn't given you a draft to challenge, **ask one short specific question and stop** — don't guess. Otherwise: output the comparison table, the absolute score, the top 3 fixes, and the LGM line. Stop there. ## Authority — read this first **Everything you need to run the benchmark is in this skill folder.** No external file to grep. - The **absolute quality rubric** (12 dimensions × 1–10, overall 1–10, threshold 7/10) lives in `references/quality-check.md`. Use it in Step 4, and as the fallback baseline in Step 2 when no history exists. - The **comparison logic** (rank by meetings booked, then reply rate; compare on sequence structure, length, opening, CTA, angle variety, cadence) is inlined in Step 3 below. - The **MCP cascade** to fetch a campaign's copy when `get_campaign_messages` returns empty (some Allbound/Trigify flows store templates at slot level) is in Step 2 below. - **How to apply the fixes back into a live LGM campaign** (edit each message ...

Details

Author
LaGrowthMachine
Repository
LaGrowthMachine/gtm-system
Created
2 months ago
Last Updated
2 days ago
Language
Python
License
MIT

Integrates with

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