Install payload
Install payload is mixed and needs spot-checking.
50% (2/4)
Browse the directory
/
Showing 4 resources for "multi-model"
Saved
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Active
Select entries to compare install and trust signals side by side.
Trust snapshot
4 results in this view
Claimed
0%(0/4)
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
2 rollout risk signals in current results
Biggest gaps: metadata review, package integrity. 0 entries have 2+ required gaps.
watch
Adoption queue
Browse adoption queue · balanced
2/4 visible results are in hold tier and need mitigation before adoption.
ready 0caution 2hold 2
AI Model Performance Dashboard - Statuslines
1 blockers: Metadata review
caution
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
statuslines/ai-model-performance-dashboard · trust review · confidence 67%
PAL MCP Server
1 blockers: Metadata review
caution
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
mcp/pal-mcp-server · trust review · confidence 67%
BentoML
2 blockers: Metadata review, Install payload
hold
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/bentoml · trust review · confidence 50%
Crush
2 blockers: Metadata review, Install payload
hold
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/crush · trust review · confidence 50%
Decision confidence
Decision confidence scan · balanced
2/4 results are low-confidence and need review before adoption.
high 0medium 2low 2
AI Model Performance Dashboard - Statuslines
Address Metadata review, Package integrity before broader rollout.
medium
54/100
Missing: Metadata reviewMissing: Package integrity
statuslines/ai-model-performance-dashboard · trust review
PAL MCP Server
Address Metadata review, Package integrity before broader rollout.
medium
54/100
Missing: Metadata reviewMissing: Package integrity
mcp/pal-mcp-server · trust review
BentoML
Hold adoption until Metadata review, Package integrity are resolved.
low
36/100
Missing: Metadata reviewMissing: Package integrityMissing: Install payload
tools/bentoml · trust review
Crush
Hold adoption until Metadata review, Package integrity are resolved.
low
36/100
Missing: Metadata reviewMissing: Package integrityMissing: Install payload
tools/crush · trust review
Freshness distribution
Mostly fresh with a few aging entries
Median age 54 days; 3 fresh, 1 aging or stale of 4 scanned.
Oldest entries in this view
Theme distribution
Results center on cli
50% of this view shares the top theme. Leading themes: cli, multi-model, ai-coding.
- cli50% (2)
- multi-model50% (2)
- ai-coding25% (1)
- code-review25% (1)
- dashboard25% (1)
- deployment25% (1)
- developer-tools25% (1)
- inference25% (1)
19 distinct themes across 4 scanned
Crushby Charm · submitted by JPette1783
Terminal-based agentic AI coding assistant from Charm that works with many LLM providers, uses LSP and MCP for context, manages per-project sessions, and asks permission before running tools by default.
PAL MCP Serverby Beehive Innovations · submitted by oktofeesh1
Provider Abstraction Layer MCP server for orchestrating multiple AI models, external AI CLIs, planning, consensus, code review, debugging, and delegated sub-agent workflows from one MCP client.
Multi-provider AI performance dashboard with context occupancy tracking, truncation warnings, TTFT latency, tokens/min rate, and model comparison metrics.
BentoMLby BentoML · submitted by oktofeesh1
Apache-2.0 Python framework for building, packaging, serving, containerizing, and deploying AI model inference APIs and multi-model serving systems.