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 Galbaz1/video-research-mcp --skill spatial-video-analysisgit clone --depth 1 https://github.com/Galbaz1/video-research-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/galbaz1/video-research-mcp/spatial-video-analysis)<a href="https://agentmods.dev/skills/galbaz1/video-research-mcp/spatial-video-analysis"><img src="https://agentmods.dev/badge/skills/galbaz1/video-research-mcp/spatial-video-analysis/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/galbaz1/video-research-mcp/spatial-video-analysis"><img src="https://agentmods.dev/badge/skills/galbaz1/video-research-mcp/spatial-video-analysis.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 | $0.00076 | $0.01116 |
| Opus 5.5 | $0.00030 | $0.00446 |
| Sonnet 5.5 | $0.00015 | $0.00223 |
| Haiku 4.5 | $0.00008 | $0.00112 |
Grade A, and why
spatial-video-analysis 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 23d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spatial video analysis source component
Installed workflow resources
For a Claude installer layout, use the adjacent managed support directory
../video-research-resources/ and its ../video-research-resources/docs/integrations/qwen-spatial.md.
The ../video-research-resources/integrations/qwen/video-spatio.json records the selected component and requirements.
Run ../video-research-resources/scripts/spatial_session.py with the explicitly selected interpreter; its adjacent helpers are installed together.
For a qualified private runtime, use ../video-research-resources/scripts/spatial_launch.py
with a trusted interpreter and -I -S -B so installed bytes are admitted before
the selected interpreter starts.
The repository-relative references below apply when using a source checkout or unpacked npm package. Installing resources does not activate optional runtimes, providers or external source components.
The component is currently runtime blocked. The selected descriptor has
runtime_clearance: blocked-missing-font-grant, a null selected executable and
no bootstrap selection. The narrow scientific profile has 41 Matplotlib legacy
AFM fonts without a mapped grant; the original profile's OpenCV/FFmpeg grant
contradiction remains retained. Neither profile may activate. The frozen
28-control geometry journey with eight authorized PNGs is UNRUN; the owned
source/stub component is not component acceptance.
Read docs/integrations/qwen-spatial.md and the current
integrations/qwen/video-spatio.json before selecting a route. The descriptor
binds 54 external source bodies, the complete Apache-2.0 LICENSE and all 19
unmodified original tool specifications at the selected revision. This
repository ships first-party adapters and attribution, without copied external
source or bundled assets. Preserve original schemas and bytes.
Use scripts/spatial_session.py through an explicit Python interpreter with
-I -B. Supply --source-root, --manifest, independently trusted
--manifest-sha256, --inputs, independently trusted --inputs-sha256, an absent
--output, and --check. The check is read-only and stdlib-only. A source/input
admitted but runtime-blocked JSON result exits 2, creates no output and imports
no foreign source or scientific package. Serving also refuses before foreign
import. Do not treat a successful source readback as runtime clearance, create
a substitute profile or run the unaccepted geometry journey.
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.
- 23d ago Changed · +14 lines 297db7183382
- 27d ago First seen · 68 lines · 76 tokens per session scan A d357ed6cb0a6
spatial-video-analysis is a skill published in the GitHub repository Galbaz1/video-research-mcp (23 stars, last pushed 5d ago), licensed MIT. It adds 76 tokens to every session and 1,116 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-03.
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