Harden contribution gate, align README counts, add signed trust attes… - #8
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…tations - validate:content now runs the prompt-injection guard on every package: critical signals (fake SYSTEM/control tokens, secret-exfil URLs) fail the build; high/medium are non-fatal warnings (legit skill prose trips the heuristic), with x_security_research opt-out. Closes the PR/git hole that the MCP upload path already covered. - README "What's inside" now distinguishes the open-seed counts in this repo (76/2/6/2) from the hosted-registry counts, instead of overstating. - New scripts/generate-trust-attestation.mjs + verify-trust-attestation.mjs: Ed25519-signed, dependency-free, offline-verifiable attestation binding a package's content hash + version to its adversarial result, so a security team can confirm a Trust Score without trusting the hosted endpoint. https://claude.ai/code/session_01CV6zb1KBVoe3eBttyK9U4Z
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…equest Infra/API follow-ups from operator feedback: - review_skills_batch: score up to 10 files in one parallel call, aligned to input order with a single shared feedback_request — far lower round-trip latency than N review_skill calls (feedback #8). - In-process result cache keyed by content_hash + options. Identical re-submissions skip both the deterministic scoring and the LLM semantic pass, cutting ~15-30s to ~0 on iterative loops; responses carry `cached` (#9). Core review logic extracted into computeReview(), shared by single + batch. - dry_run preview for upload_packages and request_primitive: validates the file (type inference + prompt-injection guard) or echoes the would-be request WITHOUT auth, persistence, or model budget, so agents can test the publish flow before connecting OAuth. The MCP write-tool auth gate now lets a dry_run call through anonymously (#5/#6). https://claude.ai/code/session_01EntkmBiYh381pKqvvSFBkg
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…tations
https://claude.ai/code/session_01CV6zb1KBVoe3eBttyK9U4Z
What does this PR add?
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version)Checklist (for content PRs)
slugand the type's folderbun run validate:contentpasses locallyNotes for reviewers