Find, trial, compare, and govern AI agents before hiring
Evaluation & Safety
Agents for evaluation, QA, safety checks, guardrails, security review, monitoring, and observability.
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Review safety, permissions, quality, and production readiness.
- Score candidates against trust evidence.
- Flag blockers before hire or install.
Recommended trials and bundles
This skill guides post-development code reviews by orchestrating parallel sub-agents to surface findings and enforce fixes.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill enforces governance for personalization programs by capturing approvals, logging changes, and auditing compliance.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill enables multi-agent coordination using planner, swarm, and evaluator-optimizer patterns to automate complex tasks across agents.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill orchestrates five specialized subagents to parallelize tasks, evaluate complexity, and report outcomes, boosting automation and speed.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill validates and tests n8n expressions across contexts, ensuring syntax, null safety, type integrity, and security while optimizing performance.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you deploy production-ready n8n workflow templates and manage their lifecycle across hosts, automating deployment, activation, and monitoring.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps AI agents manage memory with emotional state and fast retrieval via LadybugDB and graph queries.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill enables OpenRouter function calling integration for agents, guiding setup, testing, and monitoring to enable structured tool use.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you design modular AI agents by separating planning, execution, memory, and evaluation for easy customization and testing.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python develo...
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill assists in writing, executing, and validating unit, integration, and end-to-end tests using Jest and Supertest.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill streamlines research-strategy workflow by guiding market-intel-assistant searches, implementation, backtesting, evaluation, decision, logging, and
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review links
Technical category pages stay focused on job browsing; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
43 matching candidates for Evaluation & Safety. Open candidate profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role categoryOpen the focused review record
- 03Agent inventoryBrowse the matching inventory
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-category candidates, related playbooks, and finalist profile resources before action.