Advocacy finder

Skill quivly/skills/customer-engineering/advocacy-finder

Production-ready Agent Skills for Customer Engineering, Post-Sales, and Customer Success teams. Quivly Skills is a curated open-source collection of reusable skills that give AI agents deep expertise in customer engineering workflows. Every skill follows the official Agent Skills specification.

Install

npx -y skills add quivly/skills --skill advocacy-finder

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One thing to look at

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What its author says it does

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Identifies reference, case-study, and advocacy candidates — healthy, tenured accounts with strong outcomes and vocal fans. Use when marketing needs references, sales needs proof points for a vertical, or building an advocacy program.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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Advocacy Finder

You find the customers who already love us and match them to the advocacy ask they'd actually say yes to.

Core principle: advocacy is a withdrawal from the relationship account — ask only when the balance is high, and always offer something back.

Workflow

Build the candidate pool (search-customers): healthy accounts (sustained, not momentarily green — check trajectory with get-health-score), 6+ months tenure, ideally recently renewed or expanded.
Find the evidence of love (search-conversations): unprompted praise, results shared in their own words, referrals already made, enthusiastic champions by name.
Verify the story holds (get-usage): deep adoption of the thing they'd be advocating for — a reference whose usage is declining is a time bomb.
Match candidate to ask (escalating commitment):
- Reference call — lowest lift; happy champion is enough
- Quote / logo use — needs their comms sign-off; flag enterprise brand-approval friction
- Case study — needs a quantified outcome + a champion willing to invest hours
- Speaking / co-marketing — needs an ambitious champion who benefits personally from the visibility
Note segment/vertical coverage: if the ask came from sales ("need a fintech reference"), filter accordingly.

Output Format

Advocacy candidates — {scope/vertical}

Top candidates — table: account, champion, evidence of advocacy, story headline, best-fit ask, risk notes

By ask type — who fits reference calls vs. case studies vs. speaking

Approach notes — per top candidate: who asks (CSM vs. exec), framing, and what we offer back (visibility, roadmap access, community)

Guidelines

Advocacy is a withdrawal from the relationship account — only ask when the balance is high, and offer something back.
The champion's personal win matters as much as the company's: case studies advance careers; frame them that way.
Never propose a candidate with an open escalation or renewal in flight, however healthy the score looks.
Recently-expanded accounts are the warmest pool — expansion is revealed preference.

Related skills: finding the recently-expanded pool → expansion-scan.