Borrowing it
Nothing to install: this file belongs to Enriquemarq1/zernio-library-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Enriquemarq1/zernio-library-skills/main/.claude/skills/white-label-client-report/SKILL.mdgit clone --depth 1 https://github.com/Enriquemarq1/zernio-library-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/enriquemarq1/zernio-library-skills/white-label-client-report)<a href="https://agentmods.dev/skills/enriquemarq1/zernio-library-skills/white-label-client-report"><img src="https://agentmods.dev/badge/skills/enriquemarq1/zernio-library-skills/white-label-client-report/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/enriquemarq1/zernio-library-skills/white-label-client-report"><img src="https://agentmods.dev/badge/skills/enriquemarq1/zernio-library-skills/white-label-client-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00126 | $0.01972 |
| Opus 5.5 | $0.00050 | $0.00789 |
| Sonnet 5.5 | $0.00025 | $0.00394 |
| Haiku 4.5 | $0.00013 | $0.00197 |
Grade A, and why
white-label-client-report 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 4d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
White-Label Client Report: your logo on every number
Your logo. Their numbers. One API. The client opens a report with your agency's name on it, and every number on it comes from the same API that already posts, answers messages and runs ads for them.
YOUR APP → [1 YOUR LOGO] → [2 ORGANIC] → [3 PAID] → [4 RESPONSE TIME] → [5 SENTIMENT]
your link, one call, next to how fast the what people
your PDF vs last organic brand answers feel, built
period on top
The law: a report is only white-label if the client never sees anyone's name but yours, on the screen, in the link and in the PDF.
| # | Check | What proves it |
|---|---|---|
| 1 | Your logo, your link | The client opens /c/{profileId}/report or the PDF: your brand, no vendor name anywhere |
| 2 | Organic in one call | GET /v1/analytics/dashboard returns totals, followers, the daily series, top posts and the previous period at once |
| 3 | Paid next to organic | GET /v1/ads for the same client and the same dates, in the column beside organic |
| 4 | How fast the brand answers | GET /v1/analytics/inbox/response-time and /volume: median first reply, the spread, messages received |
| 5 | What people feel | Comments from GET /v1/inbox/comments, scored by your own code. Zernio gives you the raw comments; the analysis is yours to add |
Fastest path: clone the app, or paste the stages into your own. The finished app from the video, with this report built in, is in this repo at apps/white-label-app/: npm ci, npm run demo to see it on made-up data, then your key and clients.json (its README has the setup). Clone it, or read it beside the stages below while you build your own.
Starting from the blueprint app? Paste reference/stage-prompts.md one stage at a time (seven stages: the tab, organic, paid, community, sentiment, the client link and PDF, then the look) into Claude Code inside that app. Starting from your own app? Stage 0 reads your code first and keeps your framework, design and data model.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago Changed · +3 lines 72e85c31a66a
- 5d ago Changed · +12 lines 4ffe4cd638c2
- 7d ago First seen · 58 lines · 126 tokens per session scan A 822b16015b22
white-label-client-report is a skill published in the GitHub repository Enriquemarq1/zernio-library-skills (49 stars, last pushed 3d ago), licensed MIT. It adds 126 tokens to every session and 1,972 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-10-21.
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