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/practicalswan/agent-skills/deepstream-devnpx skills add PracticalSwan/agent-skills --skill deepstream-devgit clone --depth 1 https://github.com/PracticalSwan/agent-skillsWhat 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 | $0.00031 | $0.03718 |
| Opus 5 | $0.00015 | $0.01859 |
| Sonnet 5 | $0.00006 | $0.00744 |
| Haiku 4.5 | $0.00003 | $0.00372 |
Grade A, and why
deepstream-dev 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 2d 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 — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DeepStream Development Skill
When this skill is active, ALWAYS read the relevant reference documents before generating code. Do NOT rely on memory - the reference documents contain critical details about exact property names, correct API usage, and common pitfalls.
SDK and Architecture Quick Reference
DeepStream SDK Version Requirements
- GStreamer: 1.24.2
- NVIDIA Driver: 590+
- CUDA: 13.1
- TensorRT: 10.14.1.48
- Platforms: Ubuntu 24.04 (x86_64 and ARM64/Jetson)
Typical Pipeline Flow
Source → Stream Muxer → Inference → [Tracker] → OSD → Renderer
Components in [brackets] are optional -- only add them when the user explicitly requests them.
| Stage | Role | Key Element(s) | Required? |
|---|---|---|---|
| Source | Input from files, RTSP, cameras | nvurisrcbin (preferred), nvmultiurisrcbin, filesrc |
Yes |
| Stream Muxer | Batches streams for inference | nvstreammux |
Yes |
| Inference | TensorRT model execution | nvinfer, nvinferserver |
Yes |
| Tracker | Multi-object tracking across frames | nvtracker |
Only if requested |
| OSD | Draws bounding boxes, labels, overlays | nvosdbin |
Yes (for visualization) |
| Renderer | Display or save output | nveglglessink, nv3dsink, filesink |
Yes |
Memory Model
DeepStream uses NVIDIA Video Memory Manager (NVMM) for zero-copy GPU buffer transfers. Caps strings use memory:NVMM to indicate GPU memory (e.g., video/x-raw(memory:NVMM), format=NV12).
Critical Rules
- Only Add Requested Components: Do NOT add pipeline elements the user did not ask for.
- Tracker (
nvtracker): Only add when the user explicitly requests tracking or object IDs across frames - Secondary GIEs: Only add when the user requests classification or attribute extraction
- Analytics (
nvdsanalytics): Only add when the user requests line crossing, ROI counting, etc. - Message broker (
nvmsgbroker/nvmsgconv): Only add when the user requests Kafka/cloud messaging - When in doubt, build the minimal working pipeline and let the user ask for additions
- Tracker (
What ships with it
22 files 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.
- .claude-plugin/plugin.json 344 B
- BENCHMARK.md 3.7 KB
- CHANGELOG.md 3.5 KB
- evals/evals.json 6.2 KB
- references/best_practices.md 33 KB
- references/buffer_apis.md 54 KB
- references/docker_containers.md 8.7 KB
- references/gstreamer_plugins.md 31 KB
- references/kafka_messaging.md 58 KB
- references/media_extractor_advanced.md 27 KB
- references/metamux_config.md 12 KB
- references/nvds_msgapi_adapter.md 28 KB
- references/nvinfer_config.md 22 KB
- references/rest_api_dynamic.md 11 KB
- references/service_maker_api.md 61 KB
- references/streaming_sources.md 16 KB
- references/tracker_config.md 49 KB
- references/troubleshooting.md 25 KB
- references/use_cases_pipelines.md 35 KB
- references/utilities_config.md 45 KB
- skill-card.md 4.6 KB
- skill.oms.sig 8.5 KB
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.
- 2d ago First seen · 229 lines · 31 tokens per session scan A 7753ebb16775
deepstream-dev is a skill published in the GitHub repository PracticalSwan/agent-skills (11 stars, last pushed 3d ago), licensed MIT. It adds 31 tokens to every session and 3,718 once invoked, about $0.0002 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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