Borrowing it
Nothing to install: this file belongs to alecs5am/ralphy. 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/alecs5am/ralphy/main/.agents/skills/personal-clipper/SKILL.mdgit clone --depth 1 https://github.com/alecs5am/ralphyWrote 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/alecs5am/ralphy/personal-clipper)<a href="https://agentmods.dev/skills/alecs5am/ralphy/personal-clipper"><img src="https://agentmods.dev/badge/skills/alecs5am/ralphy/personal-clipper.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 19 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 22 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00174 | $0.02045 |
| Opus 5 | $0.00087 | $0.01022 |
| Sonnet 5 | $0.00035 | $0.00409 |
| Haiku 4.5 | $0.00017 | $0.00204 |
Grade A, and why
personal-clipper 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Personal clipper playbook
Turn one long-form video / stream / podcast into a handful of short vertical clips. The agent reads the source's word-level transcript, picks the strongest self-contained windows, and cuts each into a 9:16 clip through the
ralphy clipverb — then captions, renders, evaluates, and packages the survivors. This is thepersonal-clippercontent mode (#436), a supported first-class route. NOT a magic "viral moment detector": the windows are an agent decision grounded in the transcript, and the verb only executes the cut.
Sub-docs (read on demand)
| Doc | When to read it |
|---|---|
docs/playbooks/modes/personal-clipper.md |
The tight quality floor for the mode (creative objective, gates, negative scope) — read first to set the bar. |
.agents/skills/editor/SKILL.md |
Composition / caption / render mechanics once a clip is cut. |
.agents/skills/editor/references/vo-sync.md |
Snapping cut boundaries + caption timing to word-level startMs. |
.agents/skills/researcher/references/playbook.md |
Pulling the source video (ref pull) and frame/transcript tooling. |
.agents/skills/audio-explainer/SKILL.md |
The adjacent long-form-OVERLAY mode; contrast with clip-EXTRACTION here. |
When this mode fires
A brief that points at one long-form source and asks for short cuts: "cut my stream into shorts", "clip the best moments out of this podcast", "make 5 TikToks from this talk", "turn my 40-minute VOD into clips", "extract the highlights". The deterministic classifier (classifyContentMode) scores these to personal-clipper. It is a SUPPORTED route — promise it.
Contrast with the neighbours:
- A long-form video built ON TOP of the audio (overlays, faceless explainer) is
podcast-video(theaudio-explainerskill), not clip extraction. - A generated talking-head short is
ugc-review/tutorial-ugc, not a cut from an existing source.
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.
- 8d ago First seen · 81 lines · 174 tokens per session scan A e34d63ab1e09
personal-clipper is a skill published in the GitHub repository alecs5am/ralphy (131 stars, last pushed 13d ago), licensed Apache-2.0. It adds 174 tokens to every session and 2,045 once invoked, about $0.0009 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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