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 gabrielmoreira/agent-skills-mirror --skill motion-graphic-placementgit clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrorWrote 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/gabrielmoreira/agent-skills-mirror/motion-graphic-placement)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/motion-graphic-placement"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/motion-graphic-placement/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/gabrielmoreira/agent-skills-mirror/motion-graphic-placement"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/motion-graphic-placement.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 | $0.00042 | $0.00806 |
| Opus 5 | $0.00021 | $0.00403 |
| Sonnet 5 | $0.00008 | $0.00161 |
| Haiku 4.5 | $0.00004 | $0.00081 |
Grade A, and why
motion-graphic-placement 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 12d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Motion Graphic Placement
Use this skill to plan where motion graphics should appear, what type each one should be, and how to keep them readable, rhythmic, and consistent with the video.
Goals
- Reinforce important speech moments without covering the speaker or subtitles.
- Match MG type to the semantic function of the line.
- Keep density high enough for retention but sparse enough to avoid fatigue.
- Maintain one visual language across the whole edit.
Workflow
- Read project state, transcript, active design style, video aspect ratio, and visible speaker layout.
- Identify the video structure:
- hook
- problem or setup
- body / proof / steps
- summary / CTA
- Decide motion-graphic density:
- long-form landscape: usually one meaningful MG every 5-8 seconds, tighter in the first 15 seconds
- short-form portrait: usually one meaningful MG every 3-5 seconds, with stronger rhythm
- reduce density when the speaker's face, gesture, or screen recording already carries the moment
- Pick MG types from semantic triggers.
- Review the plan before generation:
- no repeated form in a row unless intentionally templated
- no overlays on face, hands, product focal point, or subtitle area
- no unnecessary full-screen takeover when a card, strip, badge, or annotation is enough
- Generate or reuse MGs.
- Place each MG against the relevant transcript moment.
- Verify screenshots at target frames and fix anything that blocks content, feels mistimed, or carries template residue.
Semantic Triggers
| Speech pattern | Good MG direction |
|---|---|
| strong opinion, conclusion, key quote | highlight sentence or quote card |
| numbers, percentages, prices | number card, counter, chart, price card |
| steps, lists, sequence | point list, flow steps, timeline |
| comparison or choice | comparison card, split card, VS card |
| warning or mistake | warning card or caution badge |
| question, suspense, hook | question card, hook text |
| self-intro, guest, role | name tag or lower-third |
| source, screenshot, comment, evidence | source card or annotation |
| CTA | CTA card |
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.
- 12d ago First seen · 75 lines · 42 tokens per session scan A 44eace41e357
motion-graphic-placement is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (17 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 806 once invoked, about $0.0002 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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