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/grayhatdevelopers/vidxp/vidxp-ingest-videonpx skills add grayhatdevelopers/vidxp --skill vidxp-ingest-videogit clone --depth 1 https://github.com/grayhatdevelopers/vidxpWrote 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/grayhatdevelopers/vidxp/vidxp-ingest-video)<a href="https://agentmods.dev/skills/grayhatdevelopers/vidxp/vidxp-ingest-video"><img src="https://agentmods.dev/badge/skills/grayhatdevelopers/vidxp/vidxp-ingest-video.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 | $0.00083 | $0.00471 |
| Opus 5 | $0.00042 | $0.00235 |
| Sonnet 5 | $0.00017 | $0.00094 |
| Haiku 4.5 | $0.00008 | $0.00047 |
Grade A, and why
vidxp-ingest-video 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 today.
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
Ingest video with VidXP
Workflow
- Resolve the
vidxpMCP tools and callget_workspace. Do not import a video that is already registered or indexed. - Choose indexable capabilities from the workspace. Use
speechandscenefor ordinary content retrieval. Addactionwhen the request depends on actions or events spanning multiple frames. Addactoronly when anonymous recurring-face clusters are wanted; it does not identify people by name. - Call
get_runtime_readiness. If selected models are missing, submitprepare_models, usewait_jobwith its observation token for subsequent bounded waits, then fetchget_jobonce when terminal. - Use
ingest_local_mediafor one to ten paths accessible to VidXP; otherwise usecreate_media_uploadand give the returned link to the user. Keepindex_after_importenabled unless registration-only behavior was requested. - Poll the returned ingestion or upload ID with
get_media_ingestionorget_media_upload. Honor its poll interval, reuse the same identifiers, and do not resubmit unchanged work. - Stop at a terminal state and report each file's state, media ID, index job,
and searchable snapshot or generation. If indexing fails after registration,
retry with
start_indexing; do not upload the file again. - If the request also asks about the video, continue directly into the VidXP evidence workflow once it is searchable.
Long operations
- Tell the user that model preparation and indexing can take several minutes.
- Update when the stage changes or about once per minute; do not narrate every status check or invent an ETA.
- Treat files independently so one failure does not hide successful siblings.
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.
- today Changed 7d4230b7d9b7
- 4d ago First seen · 37 lines · 83 tokens per session scan A 6c3bd5f5cbfe
vidxp-ingest-video is a skill published in the GitHub repository grayhatdevelopers/vidxp (30 stars, last pushed 3d ago), licensed MIT. It adds 83 tokens to every session and 471 once invoked, about $0.0004 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.
Other skills, from other repositories
native-subtitle-quote-image
将本地视频或用户有权处理的在线视频,经过来源获取、文字稿定位、选题选句、精确取帧、紧凑裁切、3:4 拼图和逐张质检,制作成视频字幕社交长图。支持两种明确分开的输出:保留画面内已烧录字幕的原生字幕模式,以及把已审核的时间点与台词绘制到真实视频帧上的脚本字幕模式。用户要求原生字幕截图、字幕帧拼图、YouTube 金句长图、台词截图、不重绘字幕、自定义中文台词,或调整主图比例、字幕区域、台词间隔和美感时使用。.
authoring-video-templates
Use when creating or editing a video template JSON (the template descriptor), adding or changing sections/filters/maps/variables/transitions/looks/motion/audio/layers, or debugging template validation errors in ffmpeg-video-composer.
core-architecture-patterns
Use when adding a segment type, platform adapter, editor manager, core service, or descriptor effect (look/grade/motion/section-audio field) in packages/ffmpeg-video-composer, or when wiring new dependencies into the tsyringe container.
ondevice-ffmpeg-engine
Use when building, modifying, or consuming the on-device FFmpeg engine — the Rust crate packages/ffmpeg-engine, the leclap-ffmpeg Expo native module, the run/probe/version/cancel API, the uniffi bindings, build-engine.sh, or the FFmpeg-from-source toolchain in scripts/ffmpeg.
reflectworld-percept
Perception automatically analyzes video segments from Eye using cloud VLM (Gemini). Working Memory tracks cross-segment event context. Results flow to ReflectWorld (storage) and Act (rules) via PostProcessor — all automatic.
reflectworld
You have access to ReflectWorld, a visual perception and persistent memory system. It gives you eyes and memory for cameras.