testimonial

testimonial is a skill for Claude Code from dansasser/claude-code-marketplace. It costs 29 tokens per session (390 once invoked), scanned A, original, MIT.

A workflow for creating a testimonial video from real customer reviews found on platforms such as Google Maps, Facebook, Yelp, Trustpilot, G2, or app stores.

In plain words
What is it for?
Use it to create videos showing ratings, review quotes, reviewer details, platform sources, and common customer themes.
Why use it?
It organises review research and turns the selected evidence into a proposed video script and animated review scenes. It also limits reviewer names to a first name and last initial for privacy.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Part of the remotion-gorombo plugin — 8 skills, 7 commands shipped together

Good fit Use it to create videos showing ratings, review quotes, reviewer details, platform sources, and common customer themes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dansasser/claude-code-marketplace/testimonial
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add dansasser/claude-code-marketplace --skill testimonial
Clone the repo
git clone --depth 1 https://github.com/dansasser/claude-code-marketplace

Made for: Claude Code.

Or install remotion-gorombo, the plugin that ships this one along with the rest of its 8 skills, 7 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for testimonial

README.md
[![agentmods](https://agentmods.dev/badge/skills/dansasser/claude-code-marketplace/testimonial.svg)](https://agentmods.dev/skills/dansasser/claude-code-marketplace/testimonial)
Your own site
<a href="https://agentmods.dev/skills/dansasser/claude-code-marketplace/testimonial"><img src="https://agentmods.dev/badge/skills/dansasser/claude-code-marketplace/testimonial.svg" alt="Measured on agentmods" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 390 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00029 $0.00390
Opus 5 $0.00015 $0.00195
Sonnet 5 $0.00006 $0.00078
Haiku 4.5 $0.00003 $0.00039

Measured 8d ago against content hash 8c0abb739f0e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

testimonial scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/remotion-gorombo/skills/testimonial/SKILL.md · 43 lines

What it actually says

Use the Remotion best practices skill (SKILL.md at the plugin root). Follow its scene planning algorithm for all production steps.

Testimonial / Social Proof

Input

$ARGUMENTS

Questionnaire

If not answered by the input, ask:

  1. What business? — Business name and/or URL
  2. Where are the reviews? — Google Maps, Facebook, Yelp, Trustpilot, G2, App Store, or should I search all?
  3. How many reviews to feature? — Default: 3-5 best ones

Script

Research reviews across all available platforms. Find:

  • Overall star rating per platform
  • Total review count
  • Top 3-5 reviews (highest rated, most compelling quotes)
  • Reviewer names (first name + last initial for privacy)
  • Any common themes across reviews

Present the findings and proposed script for approval before building.

Scene Structure

  • Scene 1: Hook — star rating reveal with count-up animation (e.g. "4.9 stars from 127 reviews")
  • Scene 2-4: Featured reviews — one review per scene, show the quote, reviewer name, star rating, and platform icon
  • Scene 5: Social proof stack — all platforms side by side with ratings, CTA

Visual Approach

  • Review cards with star ratings (gold #f59e0b)
  • Quotation mark decorative elements
  • Platform icons/logos for source attribution
  • Count-up animation for star rating and review count
  • Review cards animate in with spring, stagger between reviews
  • B-roll backgrounds matching the business type
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 43 lines · 29 tokens per session scan A 8c0abb739f0e

Subscribe to this mod's changes

testimonial is a skill published in the GitHub repository dansasser/claude-code-marketplace (9 stars, last pushed 4mo ago), licensed MIT. It adds 29 tokens to every session and 390 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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