Install payload
Install payload is broadly covered in current results.
83% (10/12)
8 trusted · 40 review · 3 limited in this set — compare to see which signals differ.
Trust signals across 40 of 51 results
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. 0 entries have 2+ required gaps.
Install payload
Install payload is broadly covered in current results.
83% (10/12)
Adoption queue
10/51 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/agent-evals-regression-gate · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/codex-plugin-creator-capability-pack · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
mcp/daloopa-mcp-server · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/google-workspace-gemini-automation · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/husky-commit-governance-capability-pack · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/model-routing-cost-latency-optimizer · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/openclaw-skill-authoring-factory-capability-pack · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/raycast-extension-dev-publish-capability-pack · trust trusted · confidence 83%
Decision confidence
7/51 results are low-confidence and need review before adoption.
Confident candidate for staged adoption.
74/100
skills/agent-evals-regression-gate · trust trusted
Confident candidate for staged adoption.
74/100
skills/codex-plugin-creator-capability-pack · trust trusted
Confident candidate for staged adoption.
74/100
mcp/daloopa-mcp-server · trust trusted
Confident candidate for staged adoption.
74/100
skills/google-workspace-gemini-automation · trust trusted
Confident candidate for staged adoption.
74/100
skills/husky-commit-governance-capability-pack · trust trusted
Confident candidate for staged adoption.
74/100
skills/model-routing-cost-latency-optimizer · trust trusted
Confident candidate for staged adoption.
74/100
skills/openclaw-skill-authoring-factory-capability-pack · trust trusted
Confident candidate for staged adoption.
74/100
skills/raycast-extension-dev-publish-capability-pack · trust trusted
Freshness distribution
Median age 82 days; 6 fresh of 12 scanned. Re-verify the oldest entries.
Oldest entries in this view
Daloopa MCP Server for Claude
Not yet verified
Google Workspace Gemini Automation Skill
Verified previously
Model Routing Cost and Latency Optimizer Skill
Verified previously
Raycast Extension Dev Publish Capability Pack Skill
Verified previously
Husky Commit Governance Capability Pack Skill
Verified previously
Theme distribution
94 distinct themes with no dominant one. Most common: data-quality, quality, ai-agents.
94 distinct themes across 24 scanned
Expert husky capability pack for lightweight local quality gates, commit message enforcement, and low-friction contributor workflows.
Expert OpenClaw skill-authoring capability pack for repeatable research, validation, packaging, and distribution workflows.
Create useful Gemini-powered Google Workspace automations for docs, sheets, email triage, and internal workflow productivity.
Design and validate model routing strategies that reduce cost and latency while preserving output quality.
Expert Raycast extension capability skill for command design, extension architecture, testing, and store-ready publication workflows.
Access high-quality fundamental financial data from SEC filings and investor presentations
The official Codacy MCP server (@codacy/codacy-mcp) that gives AI assistants access to the Codacy API for code quality, security, and coverage — listing repository and pull-request issues, retrieving file coverage and duplication, searching security (SRM) findings, inspecting analysis tools and patterns, and running local analysis with the Codacy CLI.
Connect Claude to Teradata — list databases and tables, inspect DDL, run SQL queries, preview data, analyze column quality, and explore DBA diagnostics — with the official Teradata MCP server supporting optional ML tool expansion via the teradataml Python package.
Official SonarSource MCP server that connects Claude to SonarQube Server or SonarQube Cloud for code quality, security issues, hotspots, measures, quality gates, branches, pull requests, snippets, and system context.
Apache-2.0 GX Core Python library for data quality Expectations, validation definitions, checkpoints, Data Docs, metadata stores, and pipeline quality checks.
Open-source ML and LLM observability framework for evaluating, testing, and monitoring data quality, drift, model behavior, and AI application outputs.
Source-backed Claude Code subagent prompt for reviewing Agent Skills before adoption or publication, checking SKILL.md scope, descriptions, invocation control, supporting files, tool permissions, helpfulness, safety, and privacy risks against official Claude Code skills guidance.
An agent prompt for curating an organization's Agent Skills: reviewing each SKILL.md name and description, scope (personal, project, or plugin) and precedence, per-skill allowed-tools, and whether Claude or the user invokes it.
A source-backed collection for reproducible data analysis and notebook work: Marimo notebooks, DuckDB analytical SQL, Polars DataFrames, Hugging Face Datasets loading, Great Expectations quality checks, and Streamlit sharing.
A practical guide for preparing source-backed HeyClaude content pull requests that stay focused, cite verifiable sources, avoid generated artifacts, and pass content validation.
Modern data pipeline specialist focused on real-time streaming, ETL/ELT orchestration, data quality validation, and scalable data infrastructure with Apache Airflow, dbt, and cloud-native tools
Comprehensive pre-commit hook that validates code quality, runs tests, and enforces standards.
Expert code reviewer that provides thorough, constructive feedback on code quality, security, performance, and best practices
An agent pattern for routing rapid-iteration work to Claude Haiku 4.5 — more than twice Sonnet's speed at one-third the cost ($1/$5 per million tokens) — while keeping about 90% of Sonnet 4.5's agentic-coding quality.
Build repeatable eval suites that catch quality regressions in AI agent behavior before merge or release.
Community slash command runbook for adding minimal automated tests around a changed module: inspect the git diff, mirror repository test conventions, and draft focused unit or integration tests using Anthropic develop-tests guidance.
Slash command runbook for designing and running prompt evaluations: define tasks, success criteria, golden outputs, regression checks, and privacy-safe reporting using Anthropic test-and-evaluate guidance.
Claude Code session health aggregator providing A-F grade based on cost efficiency, latency performance, productivity velocity, and cache utilization with actionable recommendations.
A user-created custom slash command that runs a red-green-refactor TDD loop in Claude Code: write failing tests first, implement until they pass, then refactor. Built with the documented custom-command frontmatter and $ARGUMENTS substitution, not a built-in feature.
Generates a comprehensive test coverage report when the coding session ends.
Comprehensive code review with security analysis, performance optimization, and best practices validation
Comprehensive code review rules for thorough analysis and constructive feedback
Open-source evaluation framework for testing RAG systems, prompts, agents, workflows, and other LLM application behavior.
Decision-assurance layer for AI agents: returns calibrated Decision Assets and an auditable action boundary (approve / review / block / seek-evidence) plus a verifiable Decision Receipt before high-stakes actions. Advisory only — never transacts or modifies identity. MCP tools: health_check and bench_query.
Source-backed rules for reviewing test code for test-double misuse, covering over-mocking that decouples tests from real behavior, under-mocking that creates slow or flaky tests, mock-return-value drift, missing contract tests for faked dependencies, and keeping test data free of personal information.