Install payload
Install payload is mixed and needs spot-checking.
67% (2/3)
Select entries to compare install and trust signals side by side.
3 results in this view
2 trust signals differ in this sample: Source provenance, Submitter
Signals differ on Source provenance, Submitter — add entries to compare before you install.
Rollout signal scan
Biggest gaps: metadata review, package integrity. 0 entries have 2+ required gaps.
Install payload
Install payload is mixed and needs spot-checking.
67% (2/3)
Most at-risk entries in this view
Adoption queue
1/3 visible results are in hold tier and need mitigation before adoption.
1 blockers: Metadata review
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
tools/cherry-studio · trust review · confidence 67%
1 blockers: Metadata review
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
collections/self-hosted-ai-operator-stack · trust review · confidence 67%
2 blockers: Metadata review, Install payload
36/100
Request metadata review from maintainers or internal owners.
Add install/config payload for reproducible team rollout.
Collect package checksum or signed artifact information.
tools/llama-cpp · trust review · confidence 50%
Decision confidence
1/3 results are low-confidence and need review before adoption.
Address Metadata review, Package integrity before broader rollout.
54/100
tools/cherry-studio · trust review
Address Metadata review, Package integrity before broader rollout.
54/100
collections/self-hosted-ai-operator-stack · trust review
Hold adoption until Metadata review, Package integrity are resolved.
36/100
tools/llama-cpp · trust review
Freshness distribution
Median age 54 days; all 3 scanned entries are within 90 days.
Theme distribution
100% of this view shares the top theme. Leading themes: local-models, inference, mcp.
16 distinct themes across 3 scanned
Cross-platform AI desktop client with multiple LLM providers, local model support, 300+ assistants, document and image handling, WebDAV backup, MCP server support, mini programs, and enterprise deployment options.
MIT-licensed C/C++ LLM inference runtime for running GGUF models locally or through a lightweight OpenAI-compatible llama-server.
A source-backed collection for operators running AI services on infrastructure they control: local model runtime, CPU and GPU inference, model gateway, self-hosted MCP access, retrieval storage, model API packaging, container rebuilds, and image security checks.