open-edge-platform/skills

Última actividad de origen registrada: 15 de octubre de 2026 a las 07:03

Catálogo de SkillsMP actualizado: 29 de octubre de 2026 a las 18:30

skills recopiladas: 22

Estrellas en GitHub: 6
Forks en GitHub: 7

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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/open-edge-platform/skills.

README del repositorio

Archivo de origen del README: README.md

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# Open Edge Platform — Agent Skills Index This repository is the central hub for **External facing agent skills** to be used by the customers to build solutions with Open Edge Platform products. ---   | Product | Skills | |---------|--------| | [Anomalib](https://github.com/open-edge-platform/anomalib) | [anomalib-adding-a-datamodule](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/anomalib-adding-a-datamodule), [anomalib-adding-a-model](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/anomalib-adding-a-model), [anomalib-benchmarking](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/anomalib-benchmarking), [anomalib-tiled-ensemble](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/anomalib-tiled-ensemble), [anomalib-training](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/anomalib-training) | | [Chat Question and Answer](https://github.com/open-edge-platform/edge-ai-libraries) | [chatqna-docker-deploy](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/chatqna-docker-deploy), [chatqna-helm-deploy](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/chatqna-helm-deploy) | | [DL Streamer](https://github.com/open-edge-platform/dlstreamer) | [dlstreamer-coding-agent](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/dlstreamer-coding-agent) | | [DL Streamer Pipeline Server](https://github.com/open-edge-platform/edge-ai-libraries) | [dlsps-user](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/dlsps-user) | | [Geti](https://github.com/open-edge-platform/geti) | [geti-using-the-pipeline](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/geti-using-the-pipeline), [getitune-discovering-models](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/getitune-discovering-models), [getitune-exporting-a-model](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/getitune-exporting-a-model), [getitune-optimizing-a-model](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/getitune-optimizing-a-model), [getitune-preparing-datasets](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/getitune-preparing-datasets), [getitune-running-inference](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/getitune-running-inference), [getitune-training-a-model](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/getitune-training-a-model) | | [Manufacturing AI Suite - AI App Builder](https://github.com/open-edge-platform/manufacturing-ai-suite) | [manufacturing-ai-app-builder](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/manufacturing-ai-app-builder) | | [Manufacturing AI Suite - App Recipe](https://github.com/open-edge-platform/manufacturing-ai-suite) | [manufacturing-app-recipe](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/manufacturing-app-recipe) | | [Metro AI Suite - AI App Builder](https://github.com/open-edge-platform/metro-ai-suite) | [metro-ai-app-builder](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/metro-ai-app-builder) | | [Metro AI Suite - Vision AI App Recipe](https://github.com/open-edge-platform/metro-ai-suite) | [metro-ai-app-recipe](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/metro-ai-app-recipe) | | [Model Download](https://github.com/open-edge-platform/edge-ai-libraries) | [model-download-user](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/model-download-user) | | [Multimodal DataPrep microservice](https://github.com/open-edge-platform/edge-ai-libraries) | [multimodal-dataprep-user](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/multimodal-dataprep-user) | | [Multimodal Embedding Serving Microservice](https://github.com/open-edge-platform/edge-ai-libraries) | [multimodal-embedding-serving-user](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/multimodal-embedding-serving-user) | | [OEP CLI Installer](https://github.com/open-edge-platform/edge-ai-libraries) | [openedge-cli](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/openedge-cli) | | [Physical AI Runtime](https://github.com/openvinotoolkit/physicalai) | [pai-configure-inference](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/pai-configure-inference), [pai-load-policy](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/pai-load-policy), [pai-run-policy](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/pai-run-policy) | | [Physical AI Train](https://github.com/open-edge-platform/physical-ai-studio) | [pai-benchmark-policy](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/pai-benchmark-policy), [pai-export-policy](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/pai-export-policy), [pai-train-policy](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/pai-train-policy), [pai-work-with-datasets](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/pai-work-with-datasets) | | [Scenescape](https://github.com/open-edge-platform/scenescape) | [scenescape-setup](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/scenescape-setup) | | [Time Series Analytics Microservice](https://github.com/open-edge-platform/edge-ai-libraries) | [time-series-analytics-user](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/time-series-analytics-user) | | [UAV Mission Compute SDK](https://github.com/open-edge-platform/federal-and-aerospace-ai-suite) | [uav-mission-compute-sdk](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/uav-mission-compute-sdk) | | [Video Search and Summarization](https://github.com/open-edge-platform/edge-ai-libraries) | [vss-deploy](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/vss-deploy), [vss-deploy-helm](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/vss-deploy-helm), [vss-search-index](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/vss-search-index), [vss-summarize-video](https://github.com/open-edge-platform/skills/tree/main/.agents/skills/vss-summarize-video) | | **Total** | **19 products, 38 skills** |  --- ## Documentation | Guide | Description | |-------|-------------| | [Overview](docs/user-guide/index.md) | What skills are and key features of this repository | | [Get Started](docs/user-guide/get-started.md) | Install, list, update, and remove skills via `npx skills` | | [How It Works](docs/user-guide/how-it-works.md) | Skill loading, index maintenance CI workflow, and lock file | | [Release Notes](docs/user-guide/release-notes.md) | Changelog and release history | ## Maintaining the Index The [`update-skills-index`](.github/workflows/update-skills-index.yml) workflow keeps this repository's README and `.agents/skills/` directory in sync automatically. It: - Runs on a **daily schedule** to pick up upstream skill changes. - Can be triggered **manually** via `workflow_dispatch` for on-demand syncs or dry-run previews. - Reads [`skills-config.json`](../../skills-config.json) as the **single source of truth** for which skills to install. - Installs or updates each skill via `npx skills add/update`, then rebuilds the skills table in the README between the `` / `` sentinels. ### Reconciliation Logic On each run the workflow: 1. **Removes** skills that are no longer in `skills-config.json` or whose configured source (repo / ref / path) has changed. 2. **Batches** remaining installs/updates by `(repo, ref)` so each source repository is cloned only once per run, regardless of how many skills it contains. 3. **Verifies** each installed skill appears in `skills-lock.json` at the expected path; falls back to a path-scoped retry if a skill is nested too deeply for the CLI's default scan depth. --- ## Contributing a Skill See [CONTRIBUTING.md](CONTRIBUTING.md) for contribution guidelines. To add a skill to the org index: 1. Create a `SKILL.md` in your repo with all the required artifacts. Supported locations (in order of convention): | Scenario | Path | |----------|------| | Standard (GitHub Copilot / VS Code) | `**/.github/skills/<skill-name>/SKILL.md` | | Agent-agnostic | `**/.agents/skills/<skill-name>/SKILL.md` | | Skills folder | `**/skills/<skill-name>/SKILL.md` | | Repo root, single skill | `SKILL.md` | Go through some of the guidelines documented at [SKILLS_GUIDE.md](./SKILLS_GUIDE.md) for defining, creating, validating and managing skills. 2. Run [skill validator](https://github.com/open-edge-platform/skills/blob/main/SKILLS_GUIDE.md#6-validation) and [skillspector](https://github.com/open-edge-platform/skills/blob/main/SKILLS_GUIDE.md#7-security-scanning) against your skills to have a clean report. ```bash # Run skill-validator tool skill-validator check --allow-dirs=evals,benchmark,example-prompts /path/to/your-skill # Run skillspector tool skillspector scan /path/to/your-skill --no-llm ``` 3. Evaluate and benchmark your skill using `tools/run_multi_cli_eval.py`. This runs your skill's `evals/evals.json` across GitHub Copilot CLI, Claude Code CLI, and OpenAI Codex CLI per configuration, grades each run with an LLM judge, and produces per-CLI and cross-CLI benchmark reports: ```bash python3 tools/run_multi_cli_eval.py \ --skill-path /path/to/your-skill \ ``` See [`tools/README.md`](tools/README.md) for the full option reference, including how to run multiple coding agents CLIs, pin specific models, skip grading, or point at non-default CLI binary paths. 4. Add an entry to `skills-config.json` in this repo and open a PR against `main`. **On every PR that touches `skills-config.json`**, the [`Check Skills Config`](.github/workflows/check-skills-config.yml) workflow runs automatically. It validates the config against its JSON schema and verifies that every newly added skill actually exists at the declared path in its source repository. **This check is a required status check — the PR cannot be merged until it passes.** Once the PR is merged, the [`Update Skills Index`](.github/workflows/update-skills-index.yml) workflow triggers automatically on the push to `main`. It installs or updates each skill via `npx skills add/update` and rebuilds the skills table in this README. The workflow also runs on a daily schedule to pick up upstream skill changes, and can be triggered manually via `workflow_dispatch` for on-demand syncs or dry-run previews.

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Stand up a complete, ready-to-run computer-vision analytics stack on Intel hardware with one Docker Compose command — point it at your video sources and an OpenVINO/ONNX model to get live annotated WebRTC video plus real-time detection dashboards and alerts…