feat(skills): integrate NVIDIA/skills as a trusted skills hub tap#34333
Merged
Conversation
Contributor
🔎 Lint report:
|
NVIDIA/skills is now a default trusted tap in the Hermes Skills Hub — discoverable, browsable, searchable, and auto-updating through the same pipeline that already serves OpenAI, Anthropic, and HuggingFace skills. Rebased onto current main.
A GitHub tap can ship a repo-root skills.sh.json (the published skills.sh
schema) declaring category groupings. The Skills Hub now reads it at index
time and uses each grouping title as the skill's category label, instead of
the tag-derived guess. Generic: any tap that ships the file gets real
categorization — NVIDIA's groupings (Inference AI, Decision Optimization,
GPU Development, etc.) flow through automatically.
- GitHubSource: _get_skillsh_groupings() fetches+caches the sidecar per repo;
_parse_skillsh_groupings() flattens it to {skill_name: title};
_list_skills_in_repo() stamps meta.extra['category']; _meta_to_dict now
serializes extra so the category survives the index cache round-trip.
- extract-skills.py: prefers extra['category'] over the tag heuristic and
exempts sidecar categories from the small-category to Other collapse.
- Docs + 12 tests.
f6f2773 to
7185a2c
Compare
This was referenced May 29, 2026
1 task
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary
NVIDIA/skillsis now a default trusted tap in the Hermes Skills Hub — discoverable, browsable, searchable, and auto-updating through the same pipeline that already serves OpenAI, Anthropic, and HuggingFace skills. On top of that, any GitHub tap (NVIDIA included) that ships a repo-rootskills.sh.jsongrouping sidecar now gets real category labels in the Skills Hub instead of a tag-derived guess.Each NVIDIA skill ships a detached OMS signature (
skill.oms.sig), an OMS-signed governanceskill-card.md, and anevals/directory; the NVIDIA sync pipeline drops any skill missing those artifacts before publishing.Changes
Tap integration
tools/skills_hub.py—NVIDIA/skillsadded toGitHubSource.DEFAULT_TAPS(path:skills/).tools/skills_guard.py—NVIDIA/skillsadded toTRUSTED_REPOSso installs resolve totrust_level="trusted".website/scripts/extract-skills.py—NVIDIA/skills→"NVIDIA"label inGITHUB_TAP_LABELS.website/src/pages/skills/index.tsx—NVIDIApill registered inSOURCE_CONFIG(green#76b900), slotted intoSOURCE_ORDERafter HuggingFace.website/docs/user-guide/features/skills.md(+zh-Hans) — NVIDIA added to default-taps and trusted-repos lists.Category groupings via
skills.sh.json(generic, not NVIDIA-specific)tools/skills_hub.py—GitHubSource._get_skillsh_groupings()fetches and caches the repo-rootskills.sh.jsonper repo;_parse_skillsh_groupings()flattens itsgroupings(eachtitle+skills[]) into{skill_name: title};_list_skills_in_repo()stamps the title ontoSkillMeta.extra["category"];_meta_to_dict()now serializesextraso the category survives the index cache round-trip.website/scripts/extract-skills.py— prefersextra["category"]over the tag heuristic, and exempts sidecar-declared categories from the small-category → "Other" collapse (so a tap's deliberate single-skill category isn't folded away).website/docs/user-guide/features/skills.md— documents theskills.sh.jsonmechanism with an example.We standardized on the published
skills.sh.jsonschema rather than NVIDIA's proprietarymetadata.json, so any future tap that adopts the standard gets categorization for free with no Hermes-side changes.Validation
tests/tools/test_skills_hub.py + test_skills_guard.pyskills.sh.json_get_skillsh_groupings(caching + no-sidecar→None)extract-skills.pyconsolidation (1-skill sidecar category survives; heuristic small-cats still collapse)Live GitHub API tested end-to-end from a fresh
HERMES_HOME. Branch rebased onto currentmain.Coordination
Per the May 28 Slack thread with @mhollinger / @moshe / @nikhilkswami (NVIDIA) — this is the integration they requested ahead of the Computex launch window. Note: NVIDIA's open PR (NVIDIA/skills#90) ships two sidecars (
metadata.json+skills.sh.json); we readskills.sh.json. Their stated launch plan is domain-only filtering, which maps cleanly onto theskills.sh.jsongroupings.