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Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

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1,672

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:testimonial-collector(推荐收藏家)
来源仓库:https://github.com/brianrwagner/ai-marketing-claude-code-skills
仓库路径:skills/testimonial-collector
安装命令:
npx skills add https://github.com/brianrwagner/ai-marketing-claude-code-skills --skill testimonial-collector
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/brianrwagner/ai-marketing-claude-code-skills --skill testimonial-collector

简介

用于辅助测试设计、自动化测试、用例整理和回归验证。

  • 适合让 Agent 编写单元测试、端到端测试或根据失败日志定位问题。
  • 使用时需确认项目测试框架、运行命令和夹具数据,避免修改真实逻辑。
  • 涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。
  • 安装方式:通过 npx skills add 命令从 GitHub 仓库安装。

SKILL.md

Testimonial Collector

Mode

Detect from context or ask: *"One script, full system, or full system with campaign?"*

ModeWhat you getBest for
quick1 outreach script + 1 format templateAsking one client, right now
standardFull collection system: timing, scripts, formatting, display guidanceBuilding repeatable social proof
deepFull system + multi-channel strategy + case study pipelineSales enablement, proposal library

Default: standard — use quick if they have one client in mind. Use deep if they want a system they can hand to a VA.


Context Loading Gates

Before proceeding, gather:

  • Client name, company, and industry
  • Project type and specific deliverables
  • Key results — push for at least one number ("even a rough estimate")
  • Desired output format (short quote / medium paragraph / full narrative)
  • Urgency (this week vs. building a library)

If results are vague (e.g., "things improved"), stop and ask: "Can you name one specific number — even a rough estimate? That's what makes a testimonial credible and usable." Do not draft until you have this.

If the user wants to skip a field: note it and flag the quality impact in the output.


Phase 1: Situation Analysis

Before drafting anything, reason through:

  1. Client relationship stage: Was this a quick project or a deep engagement? Depth affects how much authentic language is available.
  2. Results clarity: Are the outcomes measurable (numbers, timelines, named outcomes) or soft (vibes, general satisfaction)?
  3. Format match: What placement does the user need this for? A homepage needs different length than a sales deck.
  4. Voice data: Does the user have existing communication from this client (emails, Slack, quotes) that can inform tone?

Output a brief situation summary:

"You have a [length] engagement with [client] in [industry], with [strong/weak] results data. I'll draft in [format] with [authentic/templated] voice. Main gap to address: [specific gap]."

Phase 2: Quality Scoring Framework

Score the raw testimonial content (or anticipated content) before drafting:

DimensionScore 1Score 3Score 5
SpecificityNo detailsVague referencesSpecific named result
Measurability"It was great""Noticeable improvement""40% increase in leads"
Authentic VoiceSounds like ad copySlightly stiltedReads exactly how a person talks
LengthToo short (no context)Decent but thinEnough for all 3 formats

Scoring rule:

  • 4+ on all 4 dimensions → ready to use
  • ≤2 on any dimension → apply iteration protocol before delivering

Phase 3: Draft Generation

The Ask Templates

Direct Ask:

Subject: Quick favor (30 seconds)

Hey [Name],

Loved working on [project] with you — especially seeing [specific result].

Would you be open to sharing a quick testimonial I could use on my site?

No pressure. If yes, I can either:
A) Send you 3 questions to answer
B) Write a draft for you to approve/edit

Whatever's easier.

Question Route:

3 quick questions:
1. What was the situation before we worked together?
2. What changed or improved?
3. Would you recommend this to others? Why?

Draft-on-Behalf Framework: Rules for writing in the client's voice:

  • Tone: Match their actual communication style (check emails/messages for vocabulary)
  • Structure: Situation Before → What Changed → Specific Result → Recommendation
  • Avoid: Superlatives without evidence ("amazing," "life-changing")
  • Avoid: Leading with praise — lead with the client's situation
  • Length: 50-75 words (short), 100-150 words (medium), 200+ (long/full)

Fill-in template:

"[Client situation in 1 sentence]. [What the engagement delivered — concrete].
[Specific result, ideally with a number]. [Recommendation statement in client's natural voice]."

Phase 4: Format Production

Short Format (2-liner)

"[One punchy outcome sentence — lead with the result]"
— [Name], [Title] at [Company]

Use for: Homepage, LinkedIn featured section, proposal proof points

Medium Format (2-3 sentences)

"[Problem or situation]. [What changed]. [Recommendation or result]."
— [Name], [Title] at [Company]

Use for: Services page, sales decks, email sequences

Long Format (Full narrative)

Structure:

  1. Context paragraph (2-3 sentences on the situation)
  2. Transformation paragraph (what happened during the engagement)
  3. Results paragraph (outcomes, numbers, named wins)
  4. Closing recommendation sentence

Use for: Case study pages, downloadable PDFs, high-trust sales assets


Phase 5: Self-Critique Pass (REQUIRED)

After generating all formats, evaluate:

Specificity check: Does the short version have at least one concrete outcome (not just "great results")? Voice check: Could the client have actually written this, or does it sound like a marketing headline? Placement check: Is the recommended format actually correct length for the stated use case? Ethics check: Does the draft contain any claims the client didn't make or numbers you added?

Flag any issues: "The short version lacks a specific metric — you'll need to get one number from the client before using this on a homepage."


Iteration Protocol

If the received testimonial scores ≤2 on any dimension, send this gentle follow-up:

"Thanks so much — this is great. One small ask: could you add one specific
number or outcome? Even rough ('saved us about 5 hours a week') makes it
much more compelling for other clients. Totally optional, but makes a real difference."

If a second request still yields nothing specific: use Tier 3 proxy language:

"noticeable improvement in [area]" or "process now runs without manual oversight"

Placement Recommendation

Always deliver a placement recommendation with the formatted testimonials:

FormatRecommended LocationsWhy
Short (2-liner)Homepage, proposals, LinkedInTrust at first glance
MediumServices page, email, sales decksOvercome late-stage objections
LongCase study page, PDF, portfolioDeep proof for serious buyers

Cross-reference: If this client has a strong story, suggest running case-study-builder to expand into a full case study.


Output Structure

## Testimonial: [Client Name] — [Date]

### Quality Assessment
- Specificity: [X/5]
- Measurability: [X/5]
- Authentic Voice: [X/5]
- Length: [X/5]
- **Total: [X/20] — [Ready to use / Needs iteration]**

### Short Format (2-liner)
"[Quote]"
— [Name], [Title], [Company]

### Medium Format
"[Quote]"
— [Name], [Title], [Company]

### Long Format
[Full narrative]

### Placement Recommendation
[Where to use each format]

### Next Step
[Iteration note OR cross-reference to case-study-builder]

*Skill by Brian Wagner | AI Marketing Architect | brianrwagner.com*

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