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/danielrosehill/claude-video-editor-plugin/_data-storenpx skills add danielrosehill/Claude-Video-Editor-Plugin --skill _data-storegit clone --depth 1 https://github.com/danielrosehill/Claude-Video-Editor-PluginWrote 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/danielrosehill/claude-video-editor-plugin/_data-store)<a href="https://agentmods.dev/skills/danielrosehill/claude-video-editor-plugin/_data-store"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-video-editor-plugin/_data-store.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 | $0.00066 | $0.00494 |
| Opus 5 | $0.00033 | $0.00247 |
| Sonnet 5 | $0.00013 | $0.00099 |
| Haiku 4.5 | $0.00007 | $0.00049 |
Grade A, and why
data-store 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.
What it actually says
Plugin Data Store
All persistent state for this plugin lives in a single per-user directory. Skills read and write to this directory; nothing belongs under ~/.claude/.
Location
${CLAUDE_USER_DATA:-${XDG_DATA_HOME:-$HOME/.local/share}/claude-plugins}/video-editing/
Files
| File | Purpose |
|---|---|
index.json |
Path to the user's video index (base dir holding all projects) |
system-profile.json |
Detected GPU, ffmpeg encoders, codecs |
render-profiles.json |
Named, reusable render presets (codec, resolution, bitrate) |
nas.json |
NAS path / mount, raw + render destinations |
preferences.json |
Per-user prefs: EQ preset path, loudness target, default render profile, python venv path, installed tools |
presets/ |
Bundled-in copies of user-supplied presets (e.g. talking-head EQ) |
venv/ |
Shared uv-managed Python virtualenv for moviepy, auto-editor, etc. |
tools/ |
Cloned repos for tools without a PyPI release (VideoAgent, vit) |
Conventions
- All paths stored absolute (use
realpathto canonicalize). - All timestamps ISO-8601.
- Read with
jqwhen available; fall back togrep -oPfor portability. - Write atomically: write to
<file>.tmpthenmv. - Never silently overwrite — always show the existing value and ask before changing.
Linux-only assumption
This plugin assumes Linux: lspci, nvidia-smi, vainfo, pactl, rsync, ffmpeg, mlt, kdenlive. Windows or macOS users should fork and adapt.
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 · 41 lines · 66 tokens per session scan A 41caacdec285
data-store is a skill published in the GitHub repository danielrosehill/Claude-Video-Editor-Plugin (5 stars, last pushed 4mo ago), licensed MIT. It adds 66 tokens to every session and 494 once invoked, about $0.0003 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…