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.
npx skills add OneWave-AI/claude-skills --skill hyperframes-testimonial-buildergit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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.
[](https://agentmods.dev/skills/onewave-ai/claude-skills/hyperframes-testimonial-builder)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/hyperframes-testimonial-builder"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/hyperframes-testimonial-builder/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/hyperframes-testimonial-builder"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/hyperframes-testimonial-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.00901 |
| Opus 5 | $0.00034 | $0.00451 |
| Sonnet 5 | $0.00014 | $0.00180 |
| Haiku 4.5 | $0.00007 | $0.00090 |
Grade A, and why
hyperframes-testimonial-builder 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HyperFrames Testimonial Builder
Nothing sells like a customer saying it. This skill takes the proof a business already has -- Google reviews, testimonial emails, case-study numbers, NPS comments -- and directs it into renderable HyperFrames video. It owns the selection and the story; for composition mechanics, captions, transitions, and TTS, invoke the hyperframes skill (hyperframes-cli for init/lint/preview/render, hyperframes-media for voiceover).
Step 1 -- Gather the proof
Take whatever exists: pasted reviews, a review export, customer-review-aggregator output, case-study docs, or a profile URL to pull from. For each candidate quote capture the text verbatim, the name/attribution available, the specific result mentioned, and the source.
Select for specificity: "They saved us $40K and two weeks" outperforms "Great company, highly recommend" every time. Rank candidates by concrete detail, emotional arc (skeptic-to-believer beats always-happy), and relevance to the audience the video targets.
Step 2 -- Pick the format
- Spotlight (20-30s) -- one strong story: setup (the problem in the customer's words), the turn, the result, CTA.
- Review wall (15-25s) -- 4-6 short quotes in rhythm, star ratings and names, momentum building to an aggregate line ("300+ five-star reviews") and CTA.
- Proof reel (30-45s) -- stats-forward: animated counters for the numbers (customers served, dollars saved, rating), interleaved with the two best quote lines.
Step 3 -- Build the composition
- Quote text is the hero visual: large, readable, animated in phrase by phrase, timed to the VO. Attribution (first name, business/role, star row) small and consistent.
- Verbatim always -- trim with ellipses where needed, never rewrite a customer's words into marketing-speak; the texture of real speech is the credibility.
- Brand rules honored: the business's palette and type (reuse a
claude-design-system-architectordesign-style-installertoken set if present); no purple, no emoji. - Captions synced (muted autoplay is the default viewing mode), counters and star fills animated deterministically per HyperFrames seek-safety rules, VO via the media pipeline reading the quotes with a neutral warm voice -- or silence with music-bed timing if the user prefers.
- Lint and preview before declaring done; never claim it renders without running the pipeline.
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.
- 9d ago First seen · 50 lines · 68 tokens per session scan A d03640a23e66
hyperframes-testimonial-builder is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 901 once invoked, about $0.0003 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 2026-09-03.
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