agentleFS
Galbaz1Galbaz1/video-research-mcp/skills/spatial-video-analysis/SKILL.md

spatial-video-analysis

Skill23 starsChanged 38 days agoMITView on GitHub

Admit explicitly authorized PNG frames and finite spatial scene estimates for the optional pinned Qwen spatial source component. Use for source-only qualification, bounded geometry preparation, source-clock provenance, or diagnosis of its provider refusals and runtime grant block. Do not use this component as proof of physical identity, motion, visibility, calibrated geometry, or an accepted spatial runtime.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 1 is distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run ../video-research-resources/scripts/spatial_session.py with the explicitly selected interpreter.

    line 13
  2. Very specific:

    Read docs/integrations/qwen-spatial.md and the current integrations/qwen/video-spatio.json before selecting a route.

    line 27
  3. Very specific:

    Use scripts/spatial_session.py through an explicit Python interpreter with -I -B.

    line 34
  4. Distinctive:

    Only selected image/scene paths are permitted.

    line 47
  5. Very specific:

    All actual VLM dispatch is denied, including errors swallowed by upstream experts.

    line 52

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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.

Input authority selects absolute regular PNG paths with exact SHA256/byte counts, original source frame IDs and actual PTS/time-base clocks. Optional scene files need their own path/hash/byte selection. Keep at most 64 frames and 16 million pixels per PNG, strictly increasing clocks and unique paths/IDs. Only selected image/scene paths are permitted; legacy NPY/base64 branches are outside this route. Validate scene dimensions, finite cameras/intrinsics, positive depth/scale, ordered contained boxes and matching frame keys before dispatch. Reject duplicate IDs within a frame and conflicting ID labels.

All actual VLM dispatch is denied, including errors swallowed by upstream experts. Keep orientation/grounding tools advertised with provider_unavailable; never turn refusal into absence, visibility or grounding evidence. Deterministic viewpoint layout delegates the original expert without images and labels assumed facing/model orientation unverified. Refuse missing frames, missing or ambiguous viewpoint targets and unknown operations. Use the owned corrected mobile signatures rather than the original broken dispatch.

Preserve generated frame-qualified IDs and label cross-view correspondence heuristic. Caller-supplied persistent IDs are unverified assertions. Preserve two same-frame instances; refuse proximity components that could merge them. Map uniform keyframe positions back to source IDs. Missing object motion is unknown, with no stationary claim. Owned Pillow appearance segmentation uses float32 differences, explicit Pillow BILINEAR resampling, the documented strict threshold/minimum-run contract and source IDs; declare its difference from OpenCV and its lack of physical-motion proof. Point extrapolation delegates the original expert with finite 2D/3D inputs, complete outputs, at most 32 future steps and order 5.

Carry source clock/revision provenance and depth, camera, assumed FOV60 optics, identity and metric-scale caveats beside every output. Future eligible sessions must use exactly selected runtime metadata/bootstrap bytes, owned cwd/config/ cache/MPL/temp directories, credential whitelist and actual loaded-file hash receipts. The concrete launcher requires a standard-library venv with zero startup hooks and a complete installed byte inventory. Its Agg font boundary admits only 38 bundled TTFs and records font requests separately from module imports. This process has host privileges and is not a sandbox. Keep source, owned unit checks, runtime grants and physical/model acceptance as separate claims. Scoped first-party motion units using previously qualified root NumPy/Pillow remain unit evidence, with no selected-runtime qualification.

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