docs: list new skills and add external-skill vetting note
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@@ -71,6 +71,27 @@ than assuming the delegate can fetch it itself.
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actual (profane) tone -- deliberately not installed here; see
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[Mte90/linus-torvalds-skill](https://github.com/Mte90/linus-torvalds-skill)
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directly if that's ever wanted instead.
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- `code-review` -- two-axis review (Standards + Spec) of a diff against a
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fixed point, run as parallel sub-agents so neither axis masks the other.
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- `codebase-design` -- shared vocabulary for designing deep modules
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(interface, seam, depth, adapter, leverage, locality) and applying the
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deletion test.
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- `diagnosing-bugs` -- disciplined loop for hard bugs and regressions:
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build a tight feedback loop, reproduce, minimise, hypothesise,
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instrument, fix, then post-mortem.
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- `full-output-enforcement` -- override default LLM truncation; ban
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placeholder comments and partial outputs, and handle long outputs
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cleanly.
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- `handoff` -- compact the current conversation into a portable document
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so another agent can continue the work.
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- `redesign-existing-projects` -- audit an existing UI for generic AI
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patterns, then upgrade it piece by piece without rewriting the stack.
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- `research` -- delegate reading legwork to a background agent against
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primary sources, and capture cited findings as a Markdown file.
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- `resolving-merge-conflicts` -- resolve an in-progress git merge or
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rebase conflict by tracing each side's intent; never `--abort`.
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- `tdd` -- red-green-refactor test-driven development, one vertical slice
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at a time, at pre-agreed seams.
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## Provenance
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@@ -82,6 +103,21 @@ each skill's frontmatter:
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- [SuperClaude-Org/SuperClaude](https://github.com/SuperClaude-Org/SuperClaude_Framework) (MIT)
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- andrej-karpathy-skills (MIT)
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- [Mte90/linus-torvalds-skill](https://github.com/Mte90/linus-torvalds-skill) (CC0-1.0)
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- [mattpocock/skills](https://github.com/mattpocock/skills) (MIT)
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- [Leonxlnx/taste-skill](https://github.com/Leonxlnx/taste-skill) (MIT)
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## Vetting external skills
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Before installing a skill from an external repo, run NVIDIA
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[SkillSpector](https://github.com/NVIDIA/SkillSpector) against it with
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`--no-llm` (static analysis is enough for text-only skills) and review the
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report. A score of `SAFE` with no plausible issues is the default bar; if
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it reports `CAUTION`, inspect each finding manually -- most are false
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positives for skill content, but treat any that touch executable scripts,
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credential handling, or hidden instruction leakage seriously. Re-run the
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scanner on the adapted `SKILL.md` after trimming upstream-only files
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(templates, plugin metadata, sibling docs) so the result reflects what
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will actually live in this repo.
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## Adding a new skill
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