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 guimatheus92/mcp-video-analyzer --skill videogit clone --depth 1 https://github.com/guimatheus92/mcp-video-analyzerWrote 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/guimatheus92/mcp-video-analyzer/video)<a href="https://agentmods.dev/skills/guimatheus92/mcp-video-analyzer/video"><img src="https://agentmods.dev/badge/skills/guimatheus92/mcp-video-analyzer/video/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/guimatheus92/mcp-video-analyzer/video"><img src="https://agentmods.dev/badge/skills/guimatheus92/mcp-video-analyzer/video.svg" alt="Reviewed on agentmods" width="80" 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 MCP Rug Pull · line 30 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 39 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00060 | $0.01056 |
| Opus 5 | $0.00030 | $0.00528 |
| Sonnet 5 | $0.00012 | $0.00211 |
| Haiku 4.5 | $0.00006 | $0.00106 |
Grade A, and why
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 3d 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze the given video and answer the user's question (or summarize it if no question was asked). Always cite timestamps (M:SS) in your answer.
Route A — video-analyzer MCP tools available (preferred)
If the video-analyzer MCP server is connected in this session, call its tools directly — do not use the CLI:
- General question or no question →
analyze_video(detail"standard") - "What happens at X:XX" / a specific moment →
analyze_moment(time range) orget_frame_at - Question answerable from speech alone →
get_transcript(fast, no download) - Title / duration / views / comments only →
get_metadata(no download) - Motion or fast UI changes →
get_frame_burst
Dense UI capture (terminal, dashboard, IDE, spreadsheet — the meaning is in small text): pass maxWidth on any of these tools. Emitted frames are capped at 800 px wide by default, which turns a 1920×1080 screencast into 800×450 and drops a 15 px UI font below what a vision model can read. maxWidth: 0 keeps the source resolution; a value like 1568 is the middle ground. Native frames cost several times more context, so raise it for the close read, not for the overview.
Route B — no MCP server (any agent with a shell)
Run the one-shot CLI via Bash (first run downloads the npm package — slow is not broken; progress streams on stderr):
npx -y mcp-video-analyzer@latest analyze "<video-url-or-path>"
stdout is a single JSON document: metadata, transcript (timestamped entries), ocrResults (on-screen text), timeline, warnings, and frames — an array of { time, filePath, mimeType } pointing to JPEG key frames on disk. Then:
- Parse the JSON from stdout.
- Read the
frames[].filePathimages (in parallel) when the question needs visuals. - Answer from transcript + OCR + frames, citing timestamps.
Useful flags: --detail brief|standard|detailed (brief = metadata + transcript only, no frame extraction — the fast/cheap path), --fields metadata,transcript (filters the emitted JSON only; frames are still computed at standard detail), --max-frames <1-60>, --max-width <px> (frame width cap, default 800; 0 keeps source resolution — use it for dense UI captures whose payload is small text), --language <code> (force transcription language), --out <dir> (where frames are copied), --force-refresh. Run npx -y mcp-video-analyzer@latest analyze --help for the full list.
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.
- 3d ago Changed · +1 lines a914afc54c14
- 10d ago First seen · 47 lines · 60 tokens per session scan A 581526efaff3
video is a skill published in the GitHub repository guimatheus92/mcp-video-analyzer (60 stars, last pushed 3d ago), licensed MIT. It adds 60 tokens to every session and 1,056 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 2026-08-30.
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