Install payload
Install payload is sparse; verify before rollout decisions.
33% (4/12)
3 trusted · 22 review in this set — compare to see which signals differ.
25 results in this view
3 trust signals differ in this sample: Package trust, Source provenance, Submitter
Signals differ on Package trust, 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 sparse; verify before rollout decisions.
33% (4/12)
Adoption queue
14/25 visible results are in hold tier and need mitigation before adoption.
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/github-actions-ai-cicd · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/github-actions-secure-cicd-capability-pack · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/zod-schema-validator · trust trusted · confidence 83%
1 blockers: Metadata review
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
skills/dotnet-agent-skills · 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.
mcp/azure-devops-mcp-server · 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.
mcp/customerio-mcp-server · 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.
tools/dify · 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.
agents/gitlab-ci-claude-automation-agent · trust review · confidence 67%
Decision confidence
14/25 results are low-confidence and need review before adoption.
Confident candidate for staged adoption.
74/100
skills/github-actions-ai-cicd · trust trusted
Confident candidate for staged adoption.
74/100
skills/github-actions-secure-cicd-capability-pack · trust trusted
Confident candidate for staged adoption.
74/100
skills/zod-schema-validator · trust trusted
Address Metadata review, Package integrity before broader rollout.
54/100
skills/dotnet-agent-skills · trust review
Address Metadata review, Package integrity before broader rollout.
54/100
mcp/azure-devops-mcp-server · trust review
Address Metadata review, Package integrity before broader rollout.
54/100
mcp/customerio-mcp-server · trust review
Address Metadata review, Package integrity before broader rollout.
54/100
tools/dify · trust review
Address Metadata review, Package integrity before broader rollout.
54/100
agents/gitlab-ci-claude-automation-agent · trust review
Freshness distribution
Median age 55 days; 11 fresh, 1 aging or stale of 12 scanned.
Oldest entries in this view
Theme distribution
84 distinct themes with no dominant one. Most common: rag, agents, mcp.
84 distinct themes across 24 scanned
Build intelligent CI/CD pipelines with GitHub Actions, AI-assisted workflow generation, automated testing, and deployment orchestration.
Lightweight, modular open-source Python framework for building agentic AI pipelines from atomic, composable components (agents, tools, context providers), built on Instructor and Pydantic.
Production-ready LLM app and agentic workflow platform with visual workflows, RAG pipelines, agent capabilities, model management, observability, prompt IDE, APIs, Dify Cloud, and self-hosted Docker Compose deployment.
Apache-2.0 data orchestration platform for building, testing, deploying, observing, and automating data assets, jobs, schedules, sensors, and pipelines.
Official Heroku Platform MCP server that connects Claude and other MCP clients to Heroku apps, dynos, add-ons, pipelines, Private Spaces, maintenance mode, logs, deployments, one-off dynos, Heroku Postgres, and optional Heroku AI tools through the Heroku CLI.
Apache-2.0 library for pretrained diffusion model pipelines, schedulers, adapters, optimization, and training workflows for image, video, and audio generation in PyTorch.
Apache-2.0 Python workflow orchestration framework for resilient data pipelines with flows, tasks, deployments, schedules, retries, caching, workers, work pools, and observability.
Official Microsoft Azure DevOps MCP server for querying work items, pull requests, repositories, pipelines, wikis, test plans, and project metadata through remote HTTP or local stdio transports.
Open-source data and model versioning tool for tracking datasets, ML artifacts, pipelines, experiments, metrics, and remote storage alongside Git.
Open-source AI orchestration framework for building production-ready agents, RAG pipelines, multimodal search, retrieval, and tool-using LLM applications.
Open-source framework for building agentic LLM applications over private data with ingestion, indexes, retrieval, RAG, tools, workflows, and evaluation.
Apache-2.0 Python framework from Hugging Face for dense embeddings, sparse embeddings, semantic search, reranking, multimodal retrieval, and embedding-model training.
Official GitLab MCP server that connects Claude and other MCP clients to GitLab projects, issues, merge requests, pipelines, job logs, labels, work items, and semantic code search through OAuth.
Expert GitHub Actions capability skill for secure workflow architecture, token minimization, supply-chain controls, and CI reliability.
Apache-2.0 platform for programmatically authoring, scheduling, monitoring, and operating workflow DAGs across workers, executors, providers, and task logs.
TypeScript-first validation skill using Zod — define schemas once, get runtime checks and inferred types for APIs, forms, and data pipelines.
Lightweight open-source serving framework for building custom AI model inference APIs by defining a LitAPI with setup and predict methods, with batching, streaming, multi-GPU autoscaling, OpenAI-compatible endpoints, and support for compound, multimodal, RAG, and agent pipelines.
Open-source all-in-one AI framework for semantic search, LLM orchestration, and language-model workflows, built around an embeddings database that unions sparse and dense vector indexes, graph networks, and relational databases, with pipelines, workflows, agents, and web and MCP APIs.
Open-source, LLM-friendly Python web crawler and scraper that turns web pages into clean, LLM-ready Markdown for RAG, agents, and data pipelines, with an async browser pool, caching, structured extraction, and adaptive deep crawling.
Microsoft .NET team skill marketplace for AI coding agents working on .NET, C#, ASP.NET Core, Blazor, MAUI, diagnostics, MSBuild, NuGet, upgrades, tests, AI workflows, RAG pipelines, and C# MCP servers.
Access the entire Harness.io DevOps platform from Claude — CI/CD pipelines, GitOps, feature flags, cloud cost, security testing, chaos engineering, and more — through 11 consolidated tools covering 216 resource types across 36 toolsets, with 32 built-in prompt templates.
Open-source Python framework for unit-testing LLM applications, agents, RAG pipelines, metrics, regression suites, and traces.
Apache-2.0 model-definition framework for pretrained text, vision, audio, video, and multimodal models across inference, training, pipelines, generation, and fine-tuning.
Manage Customer.io from Claude — create segments, inspect customer profiles, send broadcasts and campaigns, work with journeys, and access the full Journeys UI and CDP Data Pipelines APIs — with the official Customer.io remote MCP server.
Source-backed agent that operates Claude Code inside GitLab CI pipelines — triaging pipeline failures, generating MR descriptions, running automated code review on diffs, and reporting findings back to merge requests via the GitLab API through a narrow write proxy and explicit prompt-injection boundaries.