feat(skills): add 12 Hugging Face skill entries (OCI distribution)#1124
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Adds the Hugging Face skill pack from https://github.com/huggingface/skills (Apache-2.0), pinned to upstream commit 061ab494cb145f43ae8f218939b99160e2c61c58 and packaged by Dockyard to ghcr.io/stacklok/dockyard/skills/<name>:0.1.0. Skills added: - hf-cli - hf-mcp - huggingface-community-evals - huggingface-datasets - huggingface-gradio - huggingface-llm-trainer - huggingface-paper-publisher - huggingface-papers - huggingface-tool-builder - huggingface-trackio - huggingface-vision-trainer - transformers-js Follows the OCI-distribution pattern from PRs #1093, #1094, #1095, #1109. Signed-off-by: Juan Antonio Osorio <ozz@stacklok.com>
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Summary
Adds the 12-skill Hugging Face pack from
huggingface/skillsto the ToolHive catalog. Content is Apache-2.0, pinned upstream to commit061ab49and packaged by Dockyard toghcr.io/stacklok/dockyard/skills/<name>:0.1.0(Dockyard PR #501).Follows the OCI-distribution pattern established by PR #1093 (claude-api), PR #1094 (toolhive-cli-user), PR #1095 (trailofbits security skills), and PR #1109 (gemini skills).
Skills added
hf-cli— Hugging Face Hub CLI (hf) for models, datasets, spaces, buckets, repos, jobs, inference endpoints, etc.; replaces deprecatedhuggingface-clihf-mcp— Use the Hugging Face Hub via MCP server tools (search, repo details, docs, compute jobs, Gradio Spaces as tools)huggingface-community-evals— Run HF Hub model evaluations locally with inspect-ai or lighteval (vLLM / Transformers / accelerate backends)huggingface-datasets— Dataset Viewer API workflows (rows, pagination, filters, parquet URLs, SQL via parquetlens)huggingface-gradio— Build Gradio web UIs in Python (Interface, Blocks, ChatInterface, gradio CLI)huggingface-llm-trainer— Train/fine-tune LLMs with TRL (SFT, DPO, GRPO, reward modeling) or Unsloth on HF Jobs cloud GPUs; GGUF conversionhuggingface-paper-publisher— Publish and manage research papers on HF Hub (pages, links, authorship, citations)huggingface-papers— Look up and read HF paper pages in markdown and use the papers API (arXiv IDs, structured metadata)huggingface-tool-builder— Build reusable CLI scripts using the HF API andhfCLI (composable NDJSON output, auth hygiene)huggingface-trackio— Track and visualize ML training experiments with Trackio (metrics, alerts, HF Space dashboards)huggingface-vision-trainer— Train vision models on HF Jobs (object detection, image classification, SAM/SAM2 segmentation)transformers-js— Run ML models in JavaScript/TypeScript via Transformers.js (NLP, vision, audio, multimodal; WebGPU/WASM)Notes for review
Apache-2.0. Confirmed at thehuggingface/skillsrepo root; upstream does not embed an SPDX identifier in per-skill SKILL.md frontmatter, which is tracked as an allowed Dockyard manifest issue.huggingfaceMCP server entry already in this catalog (registries/official/servers/huggingfaceandregistries/toolhive/servers/huggingface) satisfies the runtime dependency forhf-mcp,huggingface-llm-trainer, andhuggingface-vision-trainer(they callhf_jobs,hf_whoami,hf_doc_search,hf_doc_fetch).allowedTools. None of the 12 upstream SKILL.md files declareallowed-tools/allowedToolsin frontmatter.huggingface-llm-trainerreferencesmcp__huggingface__hf_whoamiin the body but not in frontmatter, so noallowedToolsis added per the frontmatter-not-body policy.hf-mcp. Itspackages[].subfolderishf-mcp/skills/hf-mcp(matches upstream repo layout); the other 11 use the standardskills/<name>subfolder.skill/SKILL.mdsubfolder. Following theclaude-api/toolhive-cli-user/gemini-*precedent — OCI is authoritative, commit-pinned git package is included as a fallback.Test plan
task catalog:validate— 32 skills total (20 existing + 12 new), all valid (both upstream and toolhive formats)task catalog:build— all 12 new skills present underdata.skillsinbuild/toolhive/registry-upstream.jsontask catalog:validatein CIregistry-upstream.jsonfeedSigned-off-by: Juan Antonio Osorio ozz@stacklok.com
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