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 agentmods add skills/jenkinsm13/resolve-mcp/import-notesnpx skills add jenkinsm13/resolve-mcp --skill import-notesgit clone --depth 1 https://github.com/jenkinsm13/resolve-mcpWrote 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/jenkinsm13/resolve-mcp/import-notes)<a href="https://agentmods.dev/skills/jenkinsm13/resolve-mcp/import-notes"><img src="https://agentmods.dev/badge/skills/jenkinsm13/resolve-mcp/import-notes.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.00686 |
| Opus 5 | $0.00015 | $0.00343 |
| Sonnet 5 | $0.00006 | $0.00137 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
import-notes 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/import-notes — Import Timecoded Notes as Markers
Paste client feedback, director's notes, or review comments with timecodes and automatically create markers on the current timeline.
Arguments
The user pastes their notes directly after the command. The notes can be in any common format — the skill parses them flexibly.
Supported Formats
Parse these timecode formats (be flexible, editors use all of them):
| Format | Example |
|---|---|
| HH:MM:SS:FF | 01:02:15:03 — fix this transition |
| HH:MM:SS | 01:02:15 needs color correction |
| MM:SS | 2:15 - cut is too abrupt |
| Seconds | 135s — bad audio here |
| Frame.io style | [01:02:15] comment text |
| Numbered list | 1. 01:02:15 — note text |
Marker Color Mapping
Automatically assign marker colors based on note content keywords:
| Keywords | Color | Meaning |
|---|---|---|
| fix, wrong, bad, error, mistake, reshoot, redo | Red | Problem |
| change, adjust, tweak, revise, update, move | Yellow | Needs attention |
| vfx, graphics, title, lower third, effect, cg | Purple | VFX/GFX needed |
| audio, sound, music, mix, levels, dialogue | Cyan | Audio note |
| love, great, perfect, approved, keep, good | Green | Approved |
| (no keyword match) | Blue | General note |
Workflow
- Use
resolve_get_timeline_infoto get fps and timeline name - Parse each note line to extract:
- Timecode (convert to frame number using timeline fps)
- Note text (everything after the timecode)
- Color (from keyword matching above)
- For each note, use
resolve_add_marker_atwith:frame: calculated frame numbercolor: auto-detected colorname: first ~40 chars of note text (truncated for marker name field)note: full note textduration: 1 frame
- Report: "Added X markers to timeline '[name]'" with a summary by color
Example Interactions
User:
/import-notes
01:02:15 — fix this transition, too abrupt
01:05:30 — love this shot, keep it
01:08:00 — need VFX cleanup on the background
01:12:45 — audio levels drop here
01:15:00 — general note: consider a different song
→ Parses 5 notes, creates Red/Green/Purple/Cyan/Blue markers respectively.
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 First seen · 77 lines · 30 tokens per session scan A cf932bee4939
import-notes is a skill published in the GitHub repository jenkinsm13/resolve-mcp (6 stars, last pushed 4mo ago), licensed MIT. It adds 30 tokens to every session and 686 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 2026-08-31.
Other skills, from other repositories
general-video
Author or edit a custom HyperFrames composition when no specialized workflow fits, or when BRIEF.md sets flow: companion. Use for longer or multi-scene pieces, brand and sizzle reels, montages, static loops, static title cards, footage remixes, and freeform builds. Use motion-graphics instead for a short unnarrated…
diagnostic-stem-delivery
Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow.
chengfeng-cut
剪辑中文口播原素材:逐词转录、词典修字出修字表、五轮扫描找口误与重复、汇总表与重复句子表、打开 Studio 让用户复核、复盘沉淀用户偏好与词典。只产出一份已复核的删词账本,不切媒体、不做字幕、不做分镜动画。用户说剪口播、处理口误、生成口播基础素材、继续剪口播,或确认卡回传 action=returncutreview 时使用。不要用于执行物理剪切、导出剪后视频、单独安装、单独打开工作台或口播分镜成片。.
chengfeng-check-updates
剪辑环境的唯一管理者:就绪检查(skills 是否最新 → Runtime 是否配套)、Skills 更新激活、Runtime 安装与体检。用户说检查更新、安装剪辑环境、装播放器、检查剪辑环境、剪辑环境就绪了吗、配置转录凭证时使用;业务 Skill(剪口播/字幕/画面/导出)第 0 步也引用本 Skill 的就绪检查。不用于剪辑、字幕、画面、导出本身或项目数据迁移。.
infographic-template-updater
Update template catalogs and UI prompts after adding new infographic templates (src/templates/.ts), including SKILL.md template list, site gallery template mappings, and the AIPlayground prompt list.
vox-director
Turn ONE topic into a finished Vox-style paper-collage explainer / ad video, end to end on the Atlas Cloud API + local ffmpeg — script, collage keyframes, motion, voice-over, music, captions, all automated. Use this whenever the user wants a "Vox style" video, a paper/torn-paper collage animation, a "motion collage"…