Vss summarize video
Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end.
npx -y skills add NVIDIA/skills --skill vss-summarize-videoAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
Use to summarize a recorded video via the LVS summarization microservice (HITL-gated) with a VLM fallback. Not for report generation or live RTSP captioning.
The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
18.4 KB, as published. Nobody here has run it
Instructions
Follow the routing tables and step-by-step workflows below. Each section that ends in workflow, quick start, or flow is intended to be executed top-to-bottom. Detailed reference material lives in references/.
Examples
Worked end-to-end examples are kept under evals/ (each *.json manifest contains a runnable scenario) and inline in the per-workflow curl blocks below. Run a Tier-3 evaluation with nv-base validate <this-skill-dir> --agent-eval to replay them.
Call the VLM NIM or the video summarization microservice directly.
Always run curl commands yourself; never instruct the user to run them.
Primary video workflow query type: "Summarize this video." Direct video summarization API and service-ops requests are handled by the reference-routed sections below.
Purpose
Produce a single, polished narrative summary of one recorded video clip, with timestamped events when the LVS microservice path is reachable.
Do NOT use this skill for:
- Live RTSP captioning — use
vss-deploy-dense-captioning. - Report generation, including incident or alert-window reports — use
vss-generate-video-reportMode B. - Semantic search across the archive — use
vss-search-archive.
Prerequisites
- VSS
lvsprofile running on$HOST_IP(port 38111) OR a reachable VLM/RT-VLM endpoint as a fallback. Thevss-deploy-profileskill brings these up. - Network reachability from the agent host to both endpoints; clip URLs from VIOS must be fetchable by the chosen backend.
jqandcurlavailable on the agent host.
Limitations
- Direct VLM fallback uses a single fixed prompt and cannot target scenario/events — output quality is lower than the LVS path.
- Remote VLM endpoints generally cannot reach
localhost/private clip URLs. - One backend call per request; no parallel hedging or multi-pass summaries.
Troubleshooting
| Symptom | Cause | Fix |
|---|---|---|
/v1/ready returns 503 repeatedly | LVS service still warming up | Retry up to ~30 s as shown in Setup; if it never returns 200 the service may not be deployed |
Empty video_summary and events | Clip does not contain the requested events | Re-run with broader scenario or different events |
VLM returns <think> block | Cosmos reasoning mode | Strip everything up to </think> before rendering |
Empty stdout from curl /v1/ready | Service legitimately returns 200 with empty body | Always check HTTP status with -o /dev/null -w '%{http_code}', never inspect the body |
See references/video-summarization-debugging.md for deeper diagnostics.
Reference Map
Use these references only when the user asks for the relevant detail, or when the core workflow below needs deeper video summarization information:
- video summarization API details:
references/video-summarization-api.mdfor/v1/summarize,/summarize,/v1/generate_captions,/v1/stream_summarize, health probes,/models,/recommended_config,/metrics, request fields, response shapes, and API gotchas. - video summarization service configuration and ops:
references/video-summarization-deployment.mdfor the VSSlvsprofile, ports, required env vars, logs, status, dry-runs, teardown, model/backend swaps, Elasticsearch/Neo4j/ArangoDB backend selection, and service-level troubleshooting. - Extended video summarization ops references:
references/video-summarization-environment-variables.md,references/video-summarization-debugging.md, andassets/video-summarization.env.example.
Load video-summarization-api.md only when you need a request field, response shape, or
endpoint that is not already covered by the Step 2 LVS or fallback VLM
example below, or when handling a direct video summarization API
request. Load video-summarization-deployment.md only for deployment,
configuration, or service operations.
Video Summarization API And Service Ops Requests
If the user asks to call or debug video summarization endpoints directly, answer from
references/video-summarization-api.md instead of running the
end-to-end video summarization workflow. Examples: list video summarization models, check
readiness, get recommended chunking config, inspect metrics, explain a 422
response, or build a /v1/summarize request body.
If the user asks to configure, deploy, restart, tear down, or troubleshoot the
video summarization service, prefer the vss-deploy-profile skill for full VSS profile
deployment and use references/video-summarization-deployment.md
for video summarization-specific service details.
Routing
Decide purely from video summarization service availability (probed in Setup → Availability checks below). Duration does not drive routing.
/v1/ready | Backend | Endpoint |
|---|---|---|
| HTTP 200 | LVS microservice with HITL | POST ${LVS_BACKEND_URL}/v1/summarize |
| Anything else | VLM / RT-VLM with the default prompt + fallback note | POST ${VLM_BASE_URL}/v1/chat/completions |
Fallback message when the LVS service is unreachable — copy verbatim above the summary:
⚠ Note: Input video
<name>is<N>s long. The video summarization service is not deployed, so this summary was produced by the VLM alone with a generic default prompt. Deploy thelvsprofile for higher-quality summaries with scenario/events targeting.
Deployment prerequisite
The VSS lvs profile on $HOST_IP is the primary backend. If the
/v1/ready probe (see Setup → Availability checks) returns anything
other than 200 after the warmup retries, ask the user:
"The VSS
lvsprofile isn't running on$HOST_IP. Shall I deploy it now using the/vss-deploy-profileskill with-p lvs? Replynoto summarize with the VLM-only fallback instead (lower quality, no scenario/events targeting)."
- Yes → hand off to
/vss-deploy-profile, then re-probe and continue with Step 2 (LVS + HITL). - No → go straight to Step 2 fallback (VLM with default prompt) and prepend the Routing fallback note. Do not ask again, and do not run scenario/events HITL.
- Pre-authorized to deploy autonomously (caller said so explicitly) → skip the confirmation and invoke
/vss-deploy-profiledirectly. - Pre-authorized to use VLM fallback ("skip lvs, just use the VLM") → go straight to Step 2 fallback without prompting.
Setup
Endpoints (defaults for a local VSS lvs deployment):
- VLM / RT-VLM:
${VLM_BASE_URL}— default${RTVI_VLM_BASE_URL:-http://${HOST_IP:-localhost}:8018} - LVS service:
${LVS_BACKEND_URL}— defaulthttp://${HOST_IP:-localhost}:38111 - VIOS: owned by
vss-manage-video-io-storage; refer there.
Use env vars when set (strip trailing /v1 from the VLM base — the skill appends it). Otherwise use the defaults. If neither works, ask the user — do not scan ports or read config files to guess.
Model name: read ${VLM_NAME} (default
nim_nvidia_cosmos3-nano-reasoner_bf16-final). It must match the id RT-VLM
/v1/models advertises; do not substitute the friendly
nvidia/cosmos3-nano-reasoner.
For endpoint schemas, optional fields, response envelopes, and error handling, see references/video-summarization-api.md.
Availability checks (run both before routing).
Readiness is determined by the HTTP status code only — the LVS
/v1/ready may legitimately return 200 with an empty body, so do not
inspect the body.
VLM="${VLM_BASE_URL:-${RTVI_VLM_BASE_URL:-http://${HOST_IP:-localhost}:8018}}"
VLM="${VLM%/v1}"
# VLM / RT-VLM: 200 on /v1/models
vlm_code=$(curl -s -o /dev/null -w '%{http_code}' --connect-timeout 3 --max-time 10 \
"$VLM/v1/models")
[ "$vlm_code" = "200" ] && echo "VLM OK" || echo "VLM not reachable (HTTP $vlm_code)"
# Video summarization service: 200 on /v1/ready, with retry on 503 (warmup) for up to ~30s
VIDEO_SUMMARIZATION_URL=${LVS_BACKEND_URL:-http://${HOST_IP:-localhost}:38111}
video_sum_code=000
for i in $(seq 1 10); do
video_sum_code=$(curl -s -o /dev/null -w '%{http_code}' --connect-timeout 3 --max-time 10 "$VIDEO_SUMMARIZATION_URL/v1/ready")
case "$video_sum_code" in
200) echo "video summarization OK"; break ;;
503) sleep 3 ;; # warming up; keep polling
*) break ;; # any other code = not reachable, stop retrying
esac
done
[ "$video_sum_code" = "200" ] || echo "video summarization service not reachable (HTTP $video_sum_code)"
How to interpret the results:
video_sum_code = 200→ Step 2 (LVS + HITL) for every video.video_sum_code != 200,vlm_code = 200→ Step 2 fallback (VLM); prepend the Routing fallback note.vlm_code != 200→ fail; at least one backend must be reachable.- A non-200 LVS code after the retry loop is the ONLY signal of unavailability. Empty stdout or missing JSON fields are NOT "unavailable."
Step 1 - Get the clip URL via vss-manage-video-io-storage (sub-task, NOT the final answer)
Use the vss-manage-video-io-storage skill for all VIOS interactions — it
owns the canonical curl recipes, parameter defaults, and delete/upload flows.
Do not fabricate URLs or hand-roll VIOS calls; they will drift.
This step is a sub-task — do NOT end your turn here; do NOT return the clip URL as the final answer. From VIOS collect three values:
streamId(viasensor/list→sensor/<id>/streams, or directly from an upload response).- Timeline -
{startTime, endTime}(ISO 8601 UTC).endTime - startTimeis the duration; needed only for the user-facing header (routing is driven solely by/v1/ready). - Temporary MP4 clip URL — the
/storage/file/<streamId>/urlvariant withcontainer=mp4. Response field:.videoUrl. Both backends need an HTTP(S) URL they canGET.
Everything else (auth, upload, disableAudio, expiry, etc.) lives in the
vss-manage-video-io-storage skill — refer users there if VIOS fails.
Step 2 — Primary: video summarization microservice with HITL
Use this path whenever /v1/ready returned 200 in Setup. Duration is irrelevant.
For advanced fields (media_info, schema, structured output, stream captioning, metrics, recommended config) see references/video-summarization-api.md.
HITL: collect scenario and events first (REQUIRED — do not skip)
Full walk-through is in references/hitl-prompts.md. Always run HITL before calling the LVS service.
Autonomous-mode defaults. When the caller has bypassed HITL ("run
autonomously without prompting") AND the original query asks for
default/defaults (or gives none), use
scenario="activity monitoring" and events=["notable activity"]
verbatim — do not infer from filename or sensor name. Note the
defaults in the final reply and offer a re-run with more specific
parameters. This is the ONLY supported HITL bypass; "the video is
short" or "the user seems in a hurry" are not valid reasons.
Prefer POST /v1/summarize (3.2 GA route); /summarize is a compatibility alias.
VIDEO_SUMMARIZATION_URL=${LVS_BACKEND_URL:-http://${HOST_IP:-localhost}:38111}
# From HITL reply:
SCENARIO='warehouse monitoring'
EVENTS_JSON='["notable activity"]'
OBJECTS_JSON='' # '' to omit, else '["forklifts","pallets","workers"]'
curl -s --max-time 300 -X POST "$VIDEO_SUMMARIZATION_URL/v1/summarize" \
-H "Content-Type: application/json" \
-d "$(jq -n --arg url "<clip_url_from_vss_manage_video_io_storage>" \
--arg model "${VLM_NAME:-nim_nvidia_cosmos3-nano-reasoner_bf16-final}" \
--arg scenario "$SCENARIO" \
--argjson events "$EVENTS_JSON" \
--argjson objects "${OBJECTS_JSON:-null}" '{
url: $url,
model: $model,
scenario: $scenario,
events: $events,
chunk_duration: 10,
num_frames_per_second_or_fixed_frames_chunk: 20,
use_fps_for_chunking: false,
seed: 1
} + (if $objects == null then {} else {objects_of_interest: $objects} end)')" \
| jq -r '.choices[0].message.content' \
| jq '{video_summary, events}'
If both video_summary and events are empty, the clip probably doesn't contain the requested events — re-run with broader scenario/events, don't report "no content".
Tuning: chunk_duration (default 10s; 0 = single chunk),
num_frames_per_second_or_fixed_frames_chunk (default 20; meaning depends
on use_fps_for_chunking), seed (default 1). num_frames_per_chunk is
deprecated.
Step 2 fallback — VLM direct with default prompt
Use this path only when /v1/ready did not return 200 after warmup. Do NOT run HITL — the user did not opt in; you fell back because the service was missing. Prepend the Routing fallback note to the response.
VLM="${VLM_BASE_URL:-${RTVI_VLM_BASE_URL:-http://${HOST_IP:-localhost}:8018}}"
VLM="${VLM%/v1}"
PROMPT='Describe in detail what is happening in this video,
including all visible people, vehicles, equipments, objects,
actions, and environmental conditions.
OUTPUT REQUIREMENTS:
[timestamp-timestamp] Description of what is happening.
EXAMPLE:
[0.0s-4.0s] <description of the first event>
[4.0s-12.0s] <description of the second event>'
curl -s --max-time 300 -X POST "$VLM/v1/chat/completions" \
-H "Content-Type: application/json" \
-d "$(jq -n \
--arg model "${VLM_NAME:-nim_nvidia_cosmos3-nano-reasoner_bf16-final}" \
--arg text "$PROMPT" \
--arg url "<clip_url_from_vss_manage_video_io_storage>" \
'{
model: $model,
temperature: 0.0,
max_tokens: 1024,
messages: [{
role: "user",
content: [
{type: "text", text: $text},
{type: "video_url", video_url: {url: $url}}
]
}]
}')" | jq -r '.choices[0].message.content'
Response: standard OpenAI chat-completion envelope. The summary is in
choices[0].message.content.
Cosmos-model notes: Cosmos models may return reasoning via
<think>...</think><answer>...</answer> blocks. Omit the reasoning
instructions if you want a plain summary. Frame sampling and pixel limits
are applied server-side; no client-side prep is required when you pass a
video_url.
End-to-end example
See references/end-to-end-example.md for
the full LVS-or-VLM-fallback script that probes /v1/ready and runs the
appropriate path.
Responses
- VLM returns an OpenAI chat-completion envelope; summary is
choices[0].message.content. - LVS service returns the same envelope but
contentis a JSON string — runjq -r '.choices[0].message.content' | jqto reach{video_summary, events}. - Errors surface as HTTP non-2xx plus JSON
{error: ...}. LVS503usually means warmup — retry/v1/ready.
Presenting the output to the user
Surface backend output with minimal transformation — do not paraphrase, re-voice, add emojis, or reformat. One backend call → one rendering: no parallel hedging, no duplicate headers, never call both LVS and VLM for the same video.
Header line. Start with exactly one:
Summary of <video_name> (<duration>)
<duration> = Ns for < 60 s, else Mm Ss (e.g. 3m 30s).
LVS output: render video_summary verbatim (polished, tone-controlled
report — rewriting loses fidelity). Render each events entry with its
start_time, end_time, type, and full description verbatim (table when
the client renders one cleanly, otherwise a per-event list). You MAY add a
one-line header and a closing offer to re-run with different parameters.
VLM output: render choices[0].message.content verbatim. If the model
produced <think>…</think><answer>…</answer> blocks, drop the <think>
block and show the answer.
Fallback warning (when applicable) goes above the summary, never mixed into it.
Tips
- Route by service availability, not by duration. Probe
/v1/readyonce in Setup; HTTP 200 → LVS+HITL for every clip; anything else → VLM fallback. - HITL is mandatory on the LVS path. The
defaultsopt-in is the only sanctioned bypass. The VLM fallback path is silent (no HITL). - Readiness = HTTP 200 on
/v1/ready. Nothing else. Body may be empty. Always usecurl -s -o /dev/null -w '%{http_code}'— never pipe throughjq/grep/head. - Delegate VIOS to
vss-manage-video-io-storage— it is a sub-task; the final answer is the Step 2 summary, not the clip URL. jqtwice for LVS output. First unwraps the OpenAI envelope, second parses the JSON string insidecontent.- Prefer
/v1/summarizefor 3.2 GA;/summarizeis a compatibility alias. - Use the exact VLM model id advertised by the endpoint (default
nim_nvidia_cosmos3-nano-reasoner_bf16-final). - Render output verbatim — no paraphrasing, no reformatting, no rewriting
the
video_summaryorchoices[0].message.content. - One call, one render. No parallel hedging, no double renderings.
- Match the image tag to the host platform. Use
LVS_TAG=3.2.1(andRTVI_VLM_IMAGE_TAG=3.2.1) on x86 / Jetson Thor, andLVS_TAG=3.2.1-sbsa(andRTVI_VLM_IMAGE_TAG=3.2.1-sbsa) on SBSA / DGX Spark / Grace (server-class ARM64) hosts.
Cross-reference
- vss-deploy-profile — bring up the
base(VLM only) orlvs(VLM + video summarization service) profile - vss-manage-video-io-storage (VIOS API) — upload videos, list streams, get clip URLs
- vss-search-archive — semantic search across the archive (different profile)
- vss-query-analytics — query incidents/events from Elasticsearch
- video summarization API reference —
references/video-summarization-api.md - video summarization service ops reference —
references/video-summarization-deployment.md
bump:3