Borrowing it
Nothing to install: this file belongs to debs-obrien/playwright-movies-app. 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/debs-obrien/playwright-movies-app/main/.github/prompts/learn-dogfood.prompt.mdgit clone --depth 1 https://github.com/debs-obrien/playwright-movies-appWrote 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/commands/debs-obrien/playwright-movies-app/learn-dogfood)<a href="https://agentmods.dev/commands/debs-obrien/playwright-movies-app/learn-dogfood"><img src="https://agentmods.dev/badge/commands/debs-obrien/playwright-movies-app/learn-dogfood/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/commands/debs-obrien/playwright-movies-app/learn-dogfood"><img src="https://agentmods.dev/badge/commands/debs-obrien/playwright-movies-app/learn-dogfood.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 | $0.00018 | $0.00087 |
| Opus 5.5 | $0.00007 | $0.00035 |
| Sonnet 5.5 | $0.00004 | $0.00017 |
| Haiku 4.5 | $0.00002 | $0.00009 |
Grade A, and why
learn-dogfood 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 26d 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.
What it actually says
Dogfood the learn path (beginner unless I name another scope).
Use the learn-dogfood skill. Walk the docs site, prefer a fresh clone for setup, execute Practice / Done when steps and exercises, then report a findings table (docs / setup / lab). Do not commit fixes unless I ask.
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.
- 26d ago First seen · 8 lines · 18 tokens per session scan A ed8deb60731c
learn-dogfood is a command published in the GitHub repository debs-obrien/playwright-movies-app (104 stars, last pushed 6d ago), licensed MIT. It adds 18 tokens to every session and 87 once invoked, about $0.0001 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 2026-10-01.
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