Skip to trial filters
Trials Trial safely Next best action: Run a sandbox trial
Trials

Trial work queue

A compact sandbox trial queue for choosing a safe first task, checking fit and trust, and opening the full review package before any local run. Use this before hiring community-sourced agents into production workflows.

925available profiles
Filter optionsRole, protocol, trust, setup, and sorting stay available here.
First queue itemiflow-mcp-sixhq-overtureReview trust and setup, then run a small code review trial.Review preflight
Setup coverage12 guided / 0 manualAcross 12 candidates on this page. A setup path is not safety approval; trust review and a sandbox trial are still required.Setup guide
Recent evidence0 runsNew sandbox evidence appears in the run ledger.Evidence queue
#1 trial priority · npm / Coding & Development
Fit
66 / 100
Trust
Needs review
Setup
MCP ready
Before run
1 check
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

MCP Server for Claude Code, Cursor, Cline, Copilot, Github Copilot, Windsurf - Visual AI Agent Plan Execution, Approval Workflow, Plan Visualization, Agent Orchestration. See what your AI is thinking before it writes code. Works with Claude, GPT, Gemini,

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • Node.js and npm: Required to run iflow-mcp-sixhq-overture.
Promotion gates
  • Clear Install path reviewed
  • Hold Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#2 trial priority · npm / Coding & Development
Fit
66 / 100
Trust
Needs review
Setup
MCP ready
Before run
1 check
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

MCP Server for Claude Code, Cursor, Cline, Copilot, Github Copilot, Windsurf - Visual AI Agent Plan Execution, Approval Workflow, Plan Visualization, Agent Orchestration. See what your AI is thinking before it writes code. Works with Claude, GPT, Gemini,

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • Node.js and npm: Required to run overture-mcp.
Promotion gates
  • Clear Install path reviewed
  • Hold Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#3 trial priority · mcpservers / Coding & Development
Fit
81 / 100
Trust
High traction
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

Scan code changes for security vulnerabilities using STRIDE threat modeling, validate findings for exploitability, and output structured results for downstream…

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#4 trial priority · aiagentsdirectory / Coding & Development
Fit
61 / 100
Trust
Needs review
Setup
MCP ready
Before run
1 check
Top risk

Stale source activityLast visible update is about 828 days old.

Full readiness snapshotCandidate summary and risk context stay available here.

AI coding agent that helps developers write code faster and smarter.

Top risk

Stale source activity: Last visible update is about 828 days old.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Hold Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#5 trial priority · mcpservers / Coding & Development
Fit
75 / 100
Trust
High traction
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

Create, update, refactor, explain, or review Microsoft Agent Framework solutions using shared guidance plus language-specific references for .NET and Python.

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#6 trial priority · mcpservers / Coding & Development
Fit
75 / 100
Trust
High traction
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

Interactive training for GitHub Copilot CLI with guided lessons, quizzes, scenarios, and reference materials. Covers slash commands, shortcuts, modes, agents, skills, MCP, and configuration through eight progressive modules Includes quiz mode (5+ questions per module), scenario challenges, and a comprehensive final exam with XP-based progression tracking Le...

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

Show 6 more trial candidatesAdditional candidates stay folded for scanning; trials.json and card resource links keep the full review path.
#7 trial priority · mcpservers / Coding & Development
Fit
75 / 100
Trust
High traction
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

Dependabot is GitHub's built-in dependency management tool with three core capabilities:

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#8 trial priority · mcpservers / Coding & Development
Fit
61 / 100
Trust
Verified source
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

Complete development kit for building Microsoft 365 Copilot declarative agents with TypeSpec and Agents Toolkit integration. Three specialized workflows cover basic agent creation, advanced enterprise design, and validation/optimization for existing agents Supports up to 5 capabilities from 11 options including WebSearch, OneDrive/SharePoint, Graph Connecto...

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#9 trial priority · mcpservers / Coding & Development
Fit
61 / 100
Trust
Verified source
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

Programmatic Power Automate flow management via FlowStudio MCP server. List, read, and monitor cloud flows directly from the Power Automate API without UI or manual steps Inspect run history, per-action error details, and trigger outputs; resubmit failed runs or cancel active executions Update flow definitions, manage connections, and retrieve HTTP-triggere...

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#10 trial priority · mcpservers / Coding & Development
Fit
61 / 100
Trust
Verified source
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

Deploy and manage MCP-based declarative agents across Microsoft 365 with admin center governance, role-based access, and organizational distribution. Supports five agent types: organization-published, creator-shared, Microsoft-native, external partner, and frontier agents, each with distinct deployment and approval workflows Provides admin controls for publ...

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#11 trial priority · mcpservers / Coding & Development
Fit
61 / 100
Trust
Verified source
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

Standard RAG re-discovers knowledge from scratch on every query. This skill is different:

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

#12 trial priority · playbooks / Coding & Development
Fit
61 / 100
Trust
Verified source
Setup
MCP ready
Before run
0 checks
Top risk

No community evaluationAgentStaffer users have not submitted a review yet.

Full readiness snapshotCandidate summary and risk context stay available here.

This skill generates high-quality PRDs for software features including executive summaries, user stories, technical specs, and risk analysis.

Top risk

No community evaluation: AgentStaffer users have not submitted a review yet.

Trial task Run a small code review trial
Input
Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
Expected output
A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
  • Clear Install path reviewed
  • Clear Trust evidence reviewed
Guardrails
  • Install asks for production credentials or broad write access.
  • Source or package cannot be verified from profile evidence.

Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.

Recent Trial Runs

RunResultScoreRolePromotionDetails
No public trial runs have been created yet. Pick a candidate above, open its profile, then use Run Trial or POST /api/actions/run-trial with the candidate listingId. New evidence appears here and in the trial guide.
Review support

Review links

Trial candidates and recent runs stay first; complete review records and finalist profile resources stay linked here.

Open Trial queue JSON
Supporting review linksLinks, review order, and page-specific notes remain available here.
Trial review paths
Trial review path
  1. 01Site contextShared review rules
  2. 02Trial queueOpen the focused review record
  3. 03Profile pageOpen the candidate page
  4. 04Profile resourcesEvidence, setup, trust, trial, and history files

Use the links and review path below for trial queue context, evidence requests, and finalist profile resources before action.

Review route: OpenAI review tools can start with openai.json; otherwise use site context and agent inventory before opening the finalist's complete review materials before install, hire, or promotion.