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 alex-durango/pingfusi --skill review-video-with-pingfusigit clone --depth 1 https://github.com/alex-durango/pingfusiWrote 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/alex-durango/pingfusi/review-video-with-pingfusi)<a href="https://agentmods.dev/skills/alex-durango/pingfusi/review-video-with-pingfusi"><img src="https://agentmods.dev/badge/skills/alex-durango/pingfusi/review-video-with-pingfusi/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/alex-durango/pingfusi/review-video-with-pingfusi"><img src="https://agentmods.dev/badge/skills/alex-durango/pingfusi/review-video-with-pingfusi.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 | $0.00136 | $0.01731 |
| Opus 5 | $0.00068 | $0.00865 |
| Sonnet 5 | $0.00027 | $0.00346 |
| Haiku 4.5 | $0.00014 | $0.00173 |
Grade A, and why
review-video-with-pingfusi 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 11d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review a video with pingfusi
A machine can render a video; it cannot tell you whether the result lands. This skill puts the video in front of a real human reviewer who scrubs it, pins comments to exact timestamps, draws on frames, answers your questions, and returns a verdict — then you fix the source, re-render, and refile until it passes.
Two shapes, one tool. Matching your own render against a brief you wrote is the iteration loop it was built for. But the brief is optional: point it at any video and ask your own questions when there is no prompt behind it to match.
Non-negotiables
- Publish before review. The reviewer is remote:
video_urlmust be a public, long-lived MP4 whose host answers Range requests with206+Content-Range(the service probes it at file time and refuses the round otherwise). A new render is a new URL — never mutate the bytes behind a URL a round already cites. - The brief must be honest, when there is one.
current_briefis what the video must match NOW. Superseded prompts go intoprompt_historymarkedreplaced— never silently dropped; the reviewer resolves conflicts by state, not guesswork.requirementsare concrete, checkable claims, each naming theprompt_idsit came from. All three are OPTIONAL: a video you did not generate from prompts you control — a competitor's ad, a tutorial, a clip someone sent you — has no brief, and you say what to judge withvideo_introandstepsinstead. - Everything except
titleis private until claim.steps,verdict_options,video_headline,video_intro, the brief, the history and the requirements all travel in a payload delivered to exactly one reviewer when they take the job, so a question may quote the brief it belongs to.titleis the opposite: it is the PUBLIC headline on the row every reviewer sees while browsing, before anyone claims. Put nothing in it you would not publish. - Ask what you actually want to know. Omit
stepsandverdict_optionsand you get the generic prompt-match questionnaire withMatches the prompt/Needs another pass, which is right for a render-against-brief loop and wrong for almost everything else. A round asking "would you keep watching past five seconds?" tells you something the generic pair cannot. - Act on feedback in the SOURCE. A timestamped comment means a fix in the composition code, the prompt, or the asset that produced that moment — never a hand-patched frame or a trimmed clip to dodge the note.
- Never approve your own render, and never infer approval from prose. Done is a
fresh
core.review.verify(stateFile)returningok === trueon the declared verdict.
What ships with it
1 file 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.
- 11d ago First seen · 124 lines · 136 tokens per session scan A 5b8796f6ba3d
review-video-with-pingfusi is a skill published in the GitHub repository alex-durango/pingfusi (112 stars, last pushed yesterday), licensed MIT. It adds 136 tokens to every session and 1,731 once invoked, about $0.0007 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 2026-08-30.
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