Test Agent Mode Prompts
Strengthen quality and coverage. Generate comprehensive tests, surface regressions early, and integrate automated checks directly into your workflow.
Platform Engineer
Standardize specs, enforce consistency, and keep your API estate clean and maintainable across teams with automated workflows powered by Agent Mode.
Validate post-deploy health by comparing New Relic metrics
Compare pre- and post-deploy metrics in New Relic for the service behind this request, surface new error groups or regressions, and summarize whether the recent deploy is healthy.
Summarize diagnostics for the latest Stainless build
Fetch the latest Stainless build diagnostics and summarize errors and warnings with suggested remediation steps.
Map all endpoints and generate a dependency map
Sends request, map dependencies, test parameter variations, and logs failures across your entire collection
Run a collection’s CI/CD tests in GitHub
Reduce manual setup and context switch and let Agent Mode run your collection tests directly inside a GitHub CI/CD workflow all from within Postman
Evaluate all API error rates over time
Analyze recent failures, find the most problematic API, and reproduces the common errors
Sync your backend code after collection changes
Agent Mode inspects updates to your collection and modifies backend code to match new routes, schemas, and expectations
Set up automated monitoring for your API
Configure a testable monitor with schedule, alerts, and failure conditions pre-applied
Sync your collections after backend changes
Agent Mode analyzes your backend code updates and syncs all affected requests, tests, and parameters in your collections
Create and commit branch with test coverage
Instantly create a branch with test coverage and send it for review in the same click
Run all tests and commit results to Git
Agent Mode runs tests, updates configs, and commits results to your Git repository
Sync backend routes into openapi.yaml
Agent Mode detects new backend routes, documents them, and updates openapi.yaml with examples and tests
Product Engineer
Automatically generate documentation, manage versioning, and create polished onboarding experiences that help internal teams and partners succeed.
Compare error rates and latency across endpoints in Amazon CloudWatch
Aggregate metrics for all collection endpoints, compare error rates and latency, and highlight the most problematic endpoints for prioritization.
Analyze Amazon CloudWatch logs for errors
Scan Amazon CloudWatch logs for the endpoint over the past 30 minutes, surface errors and warnings, and provide likely root causes and log excerpts to speed debugging.
Validate post-deploy health by comparing New Relic metrics
Compare pre- and post-deploy metrics in New Relic for the service behind this request, surface new error groups or regressions, and summarize whether the recent deploy is healthy.
Summarize diagnostics for the latest Stainless build
Fetch the latest Stainless build diagnostics and summarize errors and warnings with suggested remediation steps.
Audit MCP servers and pin dependencies with Wallarm
Scan my machine for installed MCP servers, flag risky permissions and unpinned dependencies, and generate a locked mcp.json with pinned versions for safer deployments.
Run root cause analysis on the latest Sentry issue
Locate the most recent unresolved Sentry issue, run an analysis using Seer, and summarize the issue and a recommended fix.
Use Dynatrace to investigate problems in an environment
Identify the most severe active problem in an environment, examine affected entities and related logs/traces, and compile a notebook summarizing the root cause analysis.
Create and send a test invoice via PayPal
Create and send test invoice via PayPal and return the public invoice link for verification and end-to-end testing.
Get comprehensive test coverage for your collection
Instantly generate thorough test coverage for all requests in your collection
Evaluate errors against previous ones and their resolutions
Review what worked in resolving similar past errors and test failures for faster resolutions.
Log issues in GitHub or Jira when the error needs more troubleshooting
Let Agent Mode spin up issues that automatically populate the issue description with context from the resource where the error is occurring, what's not working, and what you've tried already to fix it.
Execute commands inside this Docker container and debug services without leaving Postman
Agent Mode connects to the container behind this request and runs shell commands you specify, helping you inspect state, debug issues, and validate fixes without switching tools.
Stream live Docker container metrics as you test
Connect to a running Docker container and stream logs or metrics while you send requests, helping you observe performance and failures in real time.
Map all endpoints and generate a dependency map
Sends request, map dependencies, test parameter variations, and logs failures across your entire collection
Run a collection’s CI/CD tests in GitHub
Reduce manual setup and context switch and let Agent Mode run your collection tests directly inside a GitHub CI/CD workflow all from within Postman
Create Python server stub for your collection
Generate a server stub with validation, auth scaffolding, error handling, folder structure, and test examples
Evaluate all API error rates over time
Analyze recent failures, find the most problematic API, and reproduces the common errors
Auto-fix failing requests across the entire collection
Agent Mode executes all requests, identifies failures, patches backend issues, restarts the server, and ensures all routes return 200/201
Fix all failing tests
Runs a collection, identify every failing test, and apply targeted fixes without the toil
Sync your backend code after collection changes
Agent Mode inspects updates to your collection and modifies backend code to match new routes, schemas, and expectations
Fix backend code and get to 200 OK and save hours of debugging
Agent Mode patches backend code, restarts your server, and reruns failing requests until they return success
Set up automated monitoring for your API
Configure a testable monitor with schedule, alerts, and failure conditions pre-applied
Send requests in a collection
Execute every request and get summarized responses, headers, params, and behavior to accelerate learning
Add a new GET request to your collection
Create a new GET request with query params, path params, and example responses
Add a new POST request to your collection
Add a properly structured POST request with example payloads and parameters
Sync your collections after backend changes
Agent Mode analyzes your backend code updates and syncs all affected requests, tests, and parameters in your collections
Create and commit branch with test coverage
Instantly create a branch with test coverage and send it for review in the same click
Run all tests and commit results to Git
Agent Mode runs tests, updates configs, and commits results to your Git repository
Demystify testing
Execute your collection's entire test suite and identify failing tests with clear explanations and fixes
Detect common API errors and generate suggested fixes
Identify CORS issues, auth failures, rate limiting, missing data, versioning errors, and more - then fix them instantly
Sync backend routes into openapi.yaml
Agent Mode detects new backend routes, documents them, and updates openapi.yaml with examples and tests
QA Engineer
Increase coverage, reliability, and confidence across every API. Let Agent Mode generates comprehensive tests, surfaces regressions, and automates analysis so your team focuses on quality.
Compare error rates and latency across endpoints in Amazon CloudWatch
Aggregate metrics for all collection endpoints, compare error rates and latency, and highlight the most problematic endpoints for prioritization.
Analyze Amazon CloudWatch logs for errors
Scan Amazon CloudWatch logs for the endpoint over the past 30 minutes, surface errors and warnings, and provide likely root causes and log excerpts to speed debugging.
Validate post-deploy health by comparing New Relic metrics
Compare pre- and post-deploy metrics in New Relic for the service behind this request, surface new error groups or regressions, and summarize whether the recent deploy is healthy.
Summarize diagnostics for the latest Stainless build
Fetch the latest Stainless build diagnostics and summarize errors and warnings with suggested remediation steps.
Audit MCP servers and pin dependencies with Wallarm
Scan my machine for installed MCP servers, flag risky permissions and unpinned dependencies, and generate a locked mcp.json with pinned versions for safer deployments.
Run root cause analysis on the latest Sentry issue
Locate the most recent unresolved Sentry issue, run an analysis using Seer, and summarize the issue and a recommended fix.
Use Dynatrace to investigate problems in an environment
Identify the most severe active problem in an environment, examine affected entities and related logs/traces, and compile a notebook summarizing the root cause analysis.
Create and send a test invoice via PayPal
Create and send test invoice via PayPal and return the public invoice link for verification and end-to-end testing.
Get comprehensive test coverage for your collection
Instantly generate thorough test coverage for all requests in your collection
Evaluate errors against previous ones and their resolutions
Review what worked in resolving similar past errors and test failures for faster resolutions.
Log issues in GitHub or Jira when the error needs more troubleshooting
Let Agent Mode spin up issues that automatically populate the issue description with context from the resource where the error is occurring, what's not working, and what you've tried already to fix it.
Execute commands inside this Docker container and debug services without leaving Postman
Agent Mode connects to the container behind this request and runs shell commands you specify, helping you inspect state, debug issues, and validate fixes without switching tools.
Stream live Docker container metrics as you test
Connect to a running Docker container and stream logs or metrics while you send requests, helping you observe performance and failures in real time.
Map all endpoints and generate a dependency map
Sends request, map dependencies, test parameter variations, and logs failures across your entire collection
Run a collection’s CI/CD tests in GitHub
Reduce manual setup and context switch and let Agent Mode run your collection tests directly inside a GitHub CI/CD workflow all from within Postman
Create Python server stub for your collection
Generate a server stub with validation, auth scaffolding, error handling, folder structure, and test examples
Evaluate all API error rates over time
Analyze recent failures, find the most problematic API, and reproduces the common errors
Auto-fix failing requests across the entire collection
Agent Mode executes all requests, identifies failures, patches backend issues, restarts the server, and ensures all routes return 200/201
Fix all failing tests
Runs a collection, identify every failing test, and apply targeted fixes without the toil
Sync your backend code after collection changes
Agent Mode inspects updates to your collection and modifies backend code to match new routes, schemas, and expectations
Fix backend code and get to 200 OK and save hours of debugging
Agent Mode patches backend code, restarts your server, and reruns failing requests until they return success
Set up automated monitoring for your API
Configure a testable monitor with schedule, alerts, and failure conditions pre-applied
Send requests in a collection
Execute every request and get summarized responses, headers, params, and behavior to accelerate learning
Add a new GET request to your collection
Create a new GET request with query params, path params, and example responses
Add a new POST request to your collection
Add a properly structured POST request with example payloads and parameters
Sync your collections after backend changes
Agent Mode analyzes your backend code updates and syncs all affected requests, tests, and parameters in your collections
Create and commit branch with test coverage
Instantly create a branch with test coverage and send it for review in the same click
Run all tests and commit results to Git
Agent Mode runs tests, updates configs, and commits results to your Git repository
Demystify testing
Execute your collection's entire test suite and identify failing tests with clear explanations and fixes
Detect common API errors and generate suggested fixes
Identify CORS issues, auth failures, rate limiting, missing data, versioning errors, and more - then fix them instantly
Sync backend routes into openapi.yaml
Agent Mode detects new backend routes, documents them, and updates openapi.yaml with examples and tests
API Product Owner
Operate your APIs like products: consistent, documented, versioned, and adoption-ready. Agent Mode helps you generate clear documentation, identify breaking changes, streamline versioning, and create polished onboarding experiences that accelerate internal and partner adoption.
Create and send a test invoice via PayPal
Create and send test invoice via PayPal and return the public invoice link for verification and end-to-end testing.
Map all endpoints and generate a dependency map
Sends request, map dependencies, test parameter variations, and logs failures across your entire collection
Sync your collections after backend changes
Agent Mode analyzes your backend code updates and syncs all affected requests, tests, and parameters in your collections
Sync backend routes into openapi.yaml
Agent Mode detects new backend routes, documents them, and updates openapi.yaml with examples and tests
GTM Engineer
Create accurate, customer-specific demos and troubleshoot API issues faster. Agent Mode maps unfamiliar APIs, generates runnable examples, and automates GitHub, Jira, and Slack workflows so you can translate customer problems into solutions quickly and confidently.
Compare error rates and latency across endpoints in Amazon CloudWatch
Aggregate metrics for all collection endpoints, compare error rates and latency, and highlight the most problematic endpoints for prioritization.
Analyze Amazon CloudWatch logs for errors
Scan Amazon CloudWatch logs for the endpoint over the past 30 minutes, surface errors and warnings, and provide likely root causes and log excerpts to speed debugging.
Summarize diagnostics for the latest Stainless build
Fetch the latest Stainless build diagnostics and summarize errors and warnings with suggested remediation steps.
Audit MCP servers and pin dependencies with Wallarm
Scan my machine for installed MCP servers, flag risky permissions and unpinned dependencies, and generate a locked mcp.json with pinned versions for safer deployments.
Run root cause analysis on the latest Sentry issue
Locate the most recent unresolved Sentry issue, run an analysis using Seer, and summarize the issue and a recommended fix.
Use Dynatrace to investigate problems in an environment
Identify the most severe active problem in an environment, examine affected entities and related logs/traces, and compile a notebook summarizing the root cause analysis.
Create and send a test invoice via PayPal
Create and send test invoice via PayPal and return the public invoice link for verification and end-to-end testing.
Evaluate errors against previous ones and their resolutions
Review what worked in resolving similar past errors and test failures for faster resolutions.
Log issues in GitHub or Jira when the error needs more troubleshooting
Let Agent Mode spin up issues that automatically populate the issue description with context from the resource where the error is occurring, what's not working, and what you've tried already to fix it.
Execute commands inside this Docker container and debug services without leaving Postman
Agent Mode connects to the container behind this request and runs shell commands you specify, helping you inspect state, debug issues, and validate fixes without switching tools.
Map all endpoints and generate a dependency map
Sends request, map dependencies, test parameter variations, and logs failures across your entire collection
Create Python server stub for your collection
Generate a server stub with validation, auth scaffolding, error handling, folder structure, and test examples
Evaluate all API error rates over time
Analyze recent failures, find the most problematic API, and reproduces the common errors
Auto-fix failing requests across the entire collection
Agent Mode executes all requests, identifies failures, patches backend issues, restarts the server, and ensures all routes return 200/201
Fix all failing tests
Runs a collection, identify every failing test, and apply targeted fixes without the toil
Fix backend code and get to 200 OK and save hours of debugging
Agent Mode patches backend code, restarts your server, and reruns failing requests until they return success
Send requests in a collection
Execute every request and get summarized responses, headers, params, and behavior to accelerate learning
Add a new GET request to your collection
Create a new GET request with query params, path params, and example responses
Add a new POST request to your collection
Add a properly structured POST request with example payloads and parameters
Sync your collections after backend changes
Agent Mode analyzes your backend code updates and syncs all affected requests, tests, and parameters in your collections
Demystify testing
Execute your collection's entire test suite and identify failing tests with clear explanations and fixes
Detect common API errors and generate suggested fixes
Identify CORS issues, auth failures, rate limiting, missing data, versioning errors, and more - then fix them instantly
Popular Prompts
Evaluate errors against previous ones and their resolutions
Review what worked in resolving similar past errors and test failures for faster resolutions.
Log issues in GitHub or Jira when the error needs more troubleshooting
Let Agent Mode spin up issues that automatically populate the issue description with context from the resource where the error is occurring, what's not working, and what you've tried already to fix it.
Generate a Python SDK for your collection
Generate a production-ready Python SDK with built-in error handling, retries, and example scripts
Refactor monolithic API spec and save hours
Split a monolithic API spec into domain-based APIs and get new OpenAPI files for each in just minutes
