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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.

10available profiles
Filter optionsRole, protocol, trust, setup, and sorting stay available here.
First queue itemesimpal-api skill by openclaw/skillsReview trust and setup, then run a small code review trial.Review preflight
Setup coverage10 guided / 0 manualAcross 10 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 · playbooks / Coding & Development
Fit
61 / 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.

This skill helps you design and test agents integrating the eSIMPal API to buy, create orders, and deliver activation securely with approvals.

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
  • 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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
#2 trial priority · explainx / Coding & Development
Fit
61 / 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.

AI Native QA Agent-as-a-Service

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
  • 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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
#3 trial priority · explainx / Coding & Development
Fit
61 / 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.

AI Agent Visual Marketplace

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
  • 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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
#4 trial priority · playbooks / Workflow Automation
Fit
61 / 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.

This skill automates HackerOne workflows by parsing scope CSVs, deploying parallel pentest agents, validating PoCs, and generating ready-to-submit reports.

Top risk

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

Trial task Run a dry-run workflow trial
Input
Connect the workflow to mock inputs and ask it to produce a trace without touching production systems.
Expected output
A step-by-step run log with inputs, outputs, failures, and rollback notes.
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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
#5 trial priority · awesomeskill / Coding & Development
Fit
56 / 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.

Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add tools/capabilities, defer capability loading, stream output, define agents from YAML, or test agent behavior.

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
  • 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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
#6 trial priority · claudemarketplaces / Coding & Development
Fit
57 / 100
Trust
Needs review
Setup
Source guide
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.

A comprehensive pre-merge quality gate that spins up parallel test agents to run unit tests, integration tests, E2E validation, security scanning, and type checking. It grades your work on a 0-10 scale across code quality, security, coverage, and API validation, then generates specific improvement suggestions. Built for the fork context with effort-aware sc...

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.
  • License review: License metadata is missing from the current public profile.
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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
Show 4 more trial candidatesAdditional candidates stay folded for scanning; trials.json and card resource links keep the full review path.
#7 trial priority · remoteopenclaw / Coding & Development
Fit
37 / 100
Trust
Needs review
Setup
Source guide
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.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

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.
  • License review: License metadata is missing from the current public profile.
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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
#8 trial priority · awesomeagents / Workflow Automation
Fit
33 / 100
Trust
Needs review
Setup
Source guide
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.

Web test Agent AI

Top risk

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

Trial task Run a dry-run workflow trial
Input
Connect the workflow to mock inputs and ask it to produce a trace without touching production systems.
Expected output
A step-by-step run log with inputs, outputs, failures, and rollback notes.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • License review: License metadata is missing from the current public profile.
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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
#9 trial priority · awesomeagents / Workflow Automation
Fit
30 / 100
Trust
Needs review
Setup
Source guide
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.

This project will implement value iteration and Q-learning. It will first test agents on Gridworld (from class), then apply them to a sim…

Top risk

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

Trial task Run a dry-run workflow trial
Input
Connect the workflow to mock inputs and ask it to produce a trace without touching production systems.
Expected output
A step-by-step run log with inputs, outputs, failures, and rollback notes.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • License review: License metadata is missing from the current public profile.
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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust JSON
#10 trial priority · agencymarketplace / Workflow Automation
Fit
28 / 100
Trust
Needs review
Setup
Source guide
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.

AI Agent Visual Marketplace

Top risk

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

Trial task Run a dry-run workflow trial
Input
Connect the workflow to mock inputs and ask it to produce a trace without touching production systems.
Expected output
A step-by-step run log with inputs, outputs, failures, and rollback notes.
Permissions & setup
  • Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
  • License review: License metadata is missing from the current public profile.
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.

Review & run trial Open profile
Review links
Profile JSON Trial JSON Setup JSON Trust 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 queue JSONEvidence requests JSONPromotion queue JSONGEO exposure JSONAgent visibility JSONResource catalog JSONSite context TXTSitemap XMLProfile package JSON
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.