Introduction
AI-powered WordPress plugins are evolving beyond content generation and conversational assistance. Modern AI integrations can retrieve website information, create posts, update WooCommerce products, analyze customer records, send notifications, and execute automated business workflows.
These capabilities often depend on tools or functions that allow an AI model to interact with the WordPress application.
For example, an AI assistant might use a tool to retrieve an order, summarize a document, create a draft post, or update a product description. Although these operations make plugins more useful, they also introduce a significant security risk: AI tool abuse.
Tool abuse occurs when an AI-powered system uses an available function in an unintended, unauthorized, excessive, or unsafe way. An attacker may manipulate the model into requesting sensitive operations, supply unexpected function arguments, exploit excessive tool permissions, or repeatedly trigger expensive operations.
For example, a customer-support chatbot may have permission to retrieve a customer's own order information. An attacker might attempt to manipulate it into requesting another customer's records. Similarly, an AI agent with access to content-management tools might be persuaded to publish or delete content without the required approval.
The problem is not limited to malicious instructions. Incorrect tool configuration, missing authorization checks, unrestricted execution handlers, and poorly controlled background jobs can also create opportunities for abuse.
A secure WordPress plugin must therefore treat every AI tool request as an untrusted operation proposal. The application should decide which tools are available, validate their arguments, verify user permissions, enforce execution limits, and control sensitive actions independently of the AI model.
This article explains how to prevent AI tool abuse in WordPress plugins using practical PHP examples, application-controlled tool registries, capability checks, resource authorization, approval workflows, monitoring, and testing strategies.
Understanding AI Tool Abuse in WordPress
AI tools are application functions that allow a model to interact with external services or perform operations through a plugin.
Depending on the integration, tools may provide access to:
WordPress posts and pages.
WooCommerce products and orders.
Customer support records.
Knowledge-base documents.
User information.
Email and notification services.
Business reports.
External APIs.
Plugin settings and automated workflows.
An AI model may select a tool based on the user's request and the tool descriptions supplied by the application.
For example, a product-management assistant may have access to these tools:
AI tool
Intended purpose
search_products
Find products that match a query
get_product_details
Retrieve authorized product information
generate_description
Generate product description text
update_product_draft
Prepare a proposed product change
publish_product_update
Apply an approved product update
The presence of a tool does not mean every user should be allowed to execute it.
A customer may be permitted to search public products but must not be allowed to modify product prices. An editor may generate content but may not have permission to publish it. An AI agent may propose a database operation, but the plugin must independently determine whether that operation is allowed.
The central security principle is simple: an AI model can request a tool operation, but WordPress must authorize and execute it.
Identify Common AI Tool Abuse Risks
AI tool abuse can occur at different stages of the tool-execution process.
Unauthorized function execution: A model attempts to call a function that is not intended for the current user or AI feature.
Argument manipulation: An attacker provides unexpected identifiers, values, or parameters to influence what a tool accesses or modifies.
Excessive tool permissions: A chatbot receives access to administrative tools that are unnecessary for its intended purpose.
Prompt injection: Malicious instructions in user messages or retrieved documents attempt to influence tool selection.
Repeated execution: An AI agent triggers the same operation multiple times, creating duplicate posts, notifications, or records.
Sensitive data retrieval: A tool retrieves customer information or internal documents outside the user's permitted access.
Unrestricted external requests: An AI-generated URL or parameter is used to make requests to an unapproved destination.
Approval bypass: A tool executes a sensitive operation without the required administrator confirmation.
Background job abuse: A queued operation continues executing after its original authorization has changed or expired.
Resource exhaustion: Repeated tool calls consume excessive hosting resources or external API credits.
These risks become more serious when tools can modify website data, access private records, or communicate with external services.
Design an Application-Controlled Tool Execution Architecture
A secure AI plugin should separate model-generated tool requests from actual WordPress execution.
Do not allow the AI provider to directly execute arbitrary PHP functions or access the database.
Instead, create a controlled execution architecture:
Authenticated WordPress User | v User Request | v AI Provider | v Proposed Tool Call | v Tool Validation | +---- Tool Allowlist | +---- Argument Validation | +---- Capability Checks | +---- Resource Authorization | +---- Execution Limits | +---- Approval Requirements | v Authorized Execution Handler | v WordPress Operation | v Result Validation | v Audit Logging
Each stage should have a clearly defined responsibility.
Tool validation confirms that the requested operation is supported.
Argument validation checks the format and permitted values of its parameters.
Capability checks verify that the current user can perform the requested operation.
Resource authorization determines whether the user can access or modify the specific record.
Execution limits restrict repeated calls, resource consumption, and unintended operations.
Approval requirements provide additional authorization for sensitive activities.
Result validation checks what the tool returns before the result is passed back to the AI model or user.
This architecture keeps WordPress in control of application behavior even when the model generates an unexpected request.
Create a Fixed Allowlist of Approved AI Tools
One of the most important protections is to define which operations an AI model is allowed to request.
Never allow the model to select arbitrary PHP function names, class methods, database statements, WordPress hooks, or executable code.
A plugin should maintain a fixed tool registry.
For example:
function kaddora_ai_get_allowed_tools() { return array( 'search_products', 'get_product_details', 'generate_description', 'summarize_document', ); }
The plugin can validate a requested tool name:
function kaddora_ai_validate_tool_name( $tool_name ) { if ( ! is_string( $tool_name ) || '' === trim( $tool_name ) ) { return new WP_Error( 'kaddora_ai_invalid_tool', 'The requested AI tool is invalid.' ); } if ( ! in_array( $tool_name, kaddora_ai_get_allowed_tools(), true ) ) { return new WP_Error( 'kaddora_ai_tool_not_allowed', 'This AI operation is not available.' ); } return true; }
This ensures that only predefined tool names can proceed to the next stage.
However, an approved tool name does not automatically authorize its use. Every tool still needs its own argument validation, capability checks, and resource-level permissions.
Give Each AI Feature Only the Tools It Needs
A common architecture mistake is exposing every available plugin tool to every AI feature.
For example, a public product chatbot may need to search products and retrieve public product details. It does not need administrative tools for deleting orders, changing user roles, or modifying plugin configuration.
Use feature-specific tool registries.
function kaddora_ai_get_support_tools() { return array( 'search_support_articles', 'retrieve_authorized_ticket', 'summarize_support_ticket', ); } function kaddora_ai_get_content_tools() { return array( 'generate_content', 'summarize_document', 'create_post_draft', ); }
A feature should receive only the tools required for its intended purpose.
This approach reduces the application's attack surface and makes permissions easier to review.
It also limits the consequences of prompt injection. Even when a model is manipulated into requesting an operation, it cannot access tools that were never made available to that feature.
Tool descriptions should also be precise. Describe the intended purpose, expected arguments, and operational restrictions without exposing unnecessary internal configuration.
Validate Every Tool Argument
Even an approved tool may receive malicious or incorrectly formatted parameters.
For example, a product-search tool may accept a search term and a maximum result count. An attacker might attempt to supply unexpected values or an extremely large limit.
Validate all arguments before execution.
function kaddora_ai_validate_product_search_arguments( $arguments ) { if ( ! is_array( $arguments ) ) { return new WP_Error( 'kaddora_ai_invalid_arguments', 'The tool arguments are invalid.' ); } if ( ! isset( $arguments['search_term'] ) || ! is_string( $arguments['search_term'] ) ) { return new WP_Error( 'kaddora_ai_invalid_search_term', 'The product search term is invalid.' ); } $search_term = sanitize_text_field( $arguments['search_term'] ); if ( '' === $search_term || strlen( $search_term ) > 200 ) { return new WP_Error( 'kaddora_ai_search_term_length', 'The search term does not meet the allowed length.' ); } $limit = isset( $arguments['limit'] ) ? absint( $arguments['limit'] ) : 10; $limit = min( max( $limit, 1 ), 20 ); return array( 'search_term' => $search_term, 'limit' => $limit, ); }
The length and result limits are illustrative and should be adjusted to the plugin's requirements.
For every tool, define a clear argument schema that specifies:
Required fields.
Optional fields.
Accepted data types.
Maximum lengths.
Allowed values.
Numeric ranges.
Resource identifier formats.
Business-specific validation rules.
Where strict schemas are required, reject unexpected properties instead of silently passing them to the execution handler.
Never treat a model-generated argument as trusted application data.
Enforce WordPress Capabilities Before Tool Execution
An AI tool may be technically available to a feature while remaining unauthorized for the current user.
For example, a product assistant may expose a product-update tool, but only users with appropriate editing capabilities should be able to use it.
WordPress provides current_user_can() to check whether a user has permission to perform an operation.
An illustrative helper could look like this:
function kaddora_ai_can_update_products() { if ( ! is_user_logged_in() ) { return false; } return current_user_can( 'edit_products' ); }
A more detailed system can map tools to capabilities:
function kaddora_ai_get_tool_capabilities() { return array( 'search_products' => 'read', 'get_product_details' => 'read', 'generate_description' => 'edit_products', 'update_product_draft' => 'edit_products', 'publish_product_update'=> 'publish_products', ); }
The capability names should reflect the actual permissions available in the installation. WooCommerce product capabilities may depend on the site's role and capability configuration.
A centralized permission check can validate the requested operation:
function kaddora_ai_user_can_execute_tool( $tool_name ) { $capabilities = kaddora_ai_get_tool_capabilities(); if ( ! isset( $capabilities[ $tool_name ] ) || ! is_user_logged_in() ) { return false; } return current_user_can( $capabilities[ $tool_name ] ); }
The capability mapping must be maintained by the application, not supplied by the AI model.
Also remember that a feature-level capability does not automatically authorize access to every record.
Verify Resource-Level Permissions
A user may have permission to use a tool but not to operate on every resource the tool can access.
For example, an editor may be permitted to update posts but should not necessarily modify every post on a website.
A support employee may be allowed to retrieve support tickets but only those assigned to their team.
Before executing a resource-specific tool, verify that the current user can access the requested record.
function kaddora_ai_can_update_post( $post_id ) { $post_id = absint( $post_id ); if ( ! $post_id ) { return false; } $post = get_post( $post_id ); if ( ! $post ) { return false; } return current_user_can( 'edit_post', $post_id ); }
For custom post types, configure the appropriate capabilities. For custom database records, implement ownership, assignment, department, or tenant authorization checks.
Never assume that a valid record ID supplied by an AI tool is proof of access.
Perform resource-level authorization immediately before the operation to reduce the risk of permissions changing between the original request and execution.
Use a Controlled Tool Dispatcher
Once the tool name and arguments have passed validation, a centralized dispatcher can route the operation to the correct application function.
Avoid dynamically calling model-generated function names.
For example, this approach is unsafe:
// Unsafe: Do not execute arbitrary model-generated callbacks. call_user_func( $ai_tool_name, $arguments );
Instead, use an explicit dispatch mechanism:
function kaddora_ai_dispatch_tool( $tool_name, $arguments ) { $validation = kaddora_ai_validate_tool_name( $tool_name ); if ( is_wp_error( $validation ) ) { return $validation; } if ( ! kaddora_ai_user_can_execute_tool( $tool_name ) ) { return new WP_Error( 'kaddora_ai_tool_permission_denied', 'You cannot perform this operation.' ); } switch ( $tool_name ) { case 'search_products': $validated_arguments = kaddora_ai_validate_product_search_arguments( $arguments ); if ( is_wp_error( $validated_arguments ) ) { return $validated_arguments; } return kaddora_ai_search_products( $validated_arguments ); case 'get_product_details': return kaddora_ai_get_authorized_product( $arguments ); case 'summarize_document': return kaddora_ai_summarize_authorized_document( $arguments ); default: return new WP_Error( 'kaddora_ai_unsupported_tool', 'The requested tool is not supported.' ); } }
The individual functions in this example represent application-specific implementations. Each one must validate its own arguments and perform the necessary resource checks.
A dispatcher should never bypass the authorization rules of the functions it calls.
Prevent AI Tools From Accessing Unrestricted Database Operations
An AI agent should not receive unrestricted access to SQL execution or arbitrary database operations.
For example, a developer should never create a tool that accepts a complete SQL statement from the model and executes it through $wpdb.
This could allow a manipulated request to access or modify sensitive database information.
Instead, expose narrowly defined tools that perform specific operations through known WordPress APIs or controlled database queries.
For example, a product-search tool should accept a search term and a validated result limit, then execute a predefined query.
When dynamic values are used in SQL, pass them through $wpdb->prepare().
Do not allow the AI model to determine database table names, SQL operators, or arbitrary query fragments.
For operations involving posts, users, and WooCommerce products, prefer appropriate WordPress and WooCommerce APIs.
The goal is to expose business capabilities rather than unrestricted database access.
Require Approval for Sensitive Tool Operations
Not all AI tool calls have the same risk.
Searching public products is different from deleting records, changing prices, publishing content, or sending bulk emails.
Classify tools according to their potential impact.
Tool category
Example
Recommended protection
Informational
Search public products
Validate and execute
Low-impact modification
Save a draft description
Check capabilities and resource permissions
High-impact operation
Delete customer records
Require explicit authorization and approval
External communication
Send bulk email
Validate recipients and require appropriate approval
For sensitive operations, the AI model should prepare a proposal rather than execute the action immediately.
For example, a product-management assistant may suggest changing the price of a product.
The plugin can present:
Product name and identifier.
Current price.
Proposed price.
Reason for the proposed change.
Requesting user.
Required approval.
An authorized administrator can then approve or reject the exact operation.
Approval should be recorded in trusted application data. The AI model must never be allowed to approve its own proposed tool call.
Before execution, verify that the proposal has not expired, the target resource still exists, the values have not changed, and the approving user still has the required permission.
Restrict Repeated Tool Calls and Resource Consumption
An AI agent may call several tools during a single task.
Without execution limits, a poorly controlled agent may repeatedly retrieve records, send requests to external services, or perform operations that consume excessive resources.
A secure plugin should establish limits for:
Tool calls per AI request.
Total execution time.
Maximum records returned.
Maximum document size.
External API requests.
Retry attempts.
Background job duration.
Sensitive operations per workflow.
For example:
function kaddora_ai_check_tool_call_limit( $count ) { $maximum_calls = 8; $count = absint( $count ); if ( $count >= $maximum_calls ) { return new WP_Error( 'kaddora_ai_tool_limit_reached', 'The AI operation exceeded its tool-call limit.' ); } return true; }
The maximum number is illustrative and should reflect the complexity of the feature.
For production implementations, enforce limits on the server. Do not accept a higher tool-call limit simply because the AI model requests it.
Also consider provider usage limits, WordPress execution constraints, concurrent requests, and the cost of external operations.
Execution limits reduce the impact of uncontrolled tool loops and repeated requests.
Prevent Unauthorized External API Requests
Some AI tools communicate with external services to retrieve information, send notifications, or update connected applications.
A major risk occurs when the AI model is allowed to choose an arbitrary URL or destination.
For example, an attacker may attempt to make an AI agent send private customer information to an unapproved external address.
The plugin should define approved provider destinations and keep authentication credentials on the server.
For fixed external integrations:
Use predefined HTTPS endpoints.
Maintain a hostname allowlist where appropriate.
Validate request arguments.
Restrict which data can be transmitted.
Avoid forwarding credentials through unexpected redirects.
Apply reasonable timeouts.
Keep SSL verification enabled.
Review external provider permissions.
Use WordPress HTTP API functions for server-side communication.
wp_safe_remote_post() and wp_safe_remote_get() provide URL safety checks, but they do not replace a fixed destination policy or the need to restrict which data a tool can transmit.
Never give an AI agent an unrestricted HTTP-request tool that can send arbitrary data to arbitrary destinations.
Secure Tool Execution Through REST API and AJAX Endpoints
AI tools may be invoked through WordPress REST API routes or AJAX handlers.
These endpoints must enforce authentication, authorization, and request validation independently.
For example:
add_action( 'rest_api_init', function () { register_rest_route( 'kaddora-ai/v1', '/execute-tool', array( 'methods' => WP_REST_Server::CREATABLE, 'callback' => 'kaddora_ai_rest_execute_tool', 'permission_callback' => 'kaddora_ai_can_use_tools', ) ); } ); function kaddora_ai_can_use_tools( $request ) { if ( ! is_user_logged_in() ) { return new WP_Error( 'kaddora_ai_authentication_required', 'Authentication is required.', array( 'status' => 401 ) ); } if ( ! current_user_can( 'use_kaddora_ai_assistant' ) ) { return new WP_Error( 'kaddora_ai_access_denied', 'You cannot use this AI feature.', array( 'status' => 403 ) ); } return true; }
The endpoint callback must still validate the requested tool, its arguments, and resource permissions before execution.
For cookie-authenticated REST requests, configure WordPress REST nonce handling appropriately.
AJAX handlers should verify their request nonce and the current user's capability.
A nonce helps protect against cross-site request forgery. It does not replace authentication, authorization, or resource-level permission checks.
Public endpoints should expose only deliberately restricted operations and must not provide access to private data simply because a visitor can submit a request.
Prevent Duplicate and Replayed Tool Operations
AI agents may retry tool calls when an external service fails or a response is delayed.
This can accidentally create duplicate records, repeated notifications, or multiple updates.
Sensitive operations should use execution identifiers or idempotency controls.
For example:
$execution_record = array( 'execution_id' => wp_generate_uuid4(), 'tool_name' => 'send_approved_notification', 'user_id' => get_current_user_id(), 'status' => 'pending', );
This is an illustrative execution record. A production plugin should store execution state persistently and verify whether the operation has already been completed before performing it again.
For operations that support provider-side idempotency keys, use them according to the external service's documented behavior.
Also prevent two concurrent requests from executing the same approval simultaneously. Use suitable transactional, locking, or atomic-state mechanisms for the chosen storage system.
Idempotency prevents duplicate execution; it does not grant permission to perform an operation. Authentication, capability checks, and resource authorization remain necessary.
Monitor and Audit AI Tool Execution
A secure WordPress plugin should record important tool-execution decisions.
Useful audit events include:
Tool request received.
Unsupported tool rejected.
Invalid arguments detected.
Capability check failed.
Resource access denied.
Approval requested.
Approval granted or rejected.
Operation executed.
Duplicate execution blocked.
Tool-call limit reached.
External request failed.
An illustrative audit structure could look like this:
$audit_event = array( 'event_id' => wp_generate_uuid4(), 'user_id' => get_current_user_id(), 'tool_name' => 'update_product_draft', 'resource_id'=> 125, 'result' => 'denied', 'reason' => 'missing_resource_permission', 'created_at' => current_time( 'mysql', true ), );
This example creates an event structure. A production plugin must store it using an appropriately protected logging mechanism.
Useful audit information includes the requesting user, tool name, resource identifier, authorization decision, approval status, execution result, request identifier, and timestamp.
Avoid recording complete prompts, private customer records, API credentials, authorization headers, or unnecessary personal information.
Protected logs help administrators investigate unauthorized attempts and understand how AI tools are being used.
Test AI Tools Against Abuse Scenarios
Tool security should be tested independently of the model's ability to generate useful responses.
Developers should simulate malicious requests and unexpected tool arguments.
Important test scenarios include:
An unauthorized user requests an administrative tool.
A model returns an unsupported function name.
An approved tool receives invalid arguments.
An editor attempts to publish content without permission.
A user requests another customer's private order.
A tool receives a resource identifier belonging to another tenant.
A retrieved document attempts to trigger a sensitive action.
A model requests an unrestricted external URL.
An approval record is expired or already used.
The same operation is submitted repeatedly.
A background task executes after the original user's permissions change.
An AI agent exceeds its permitted tool-call limit.
A REST endpoint receives an unauthorized request.
Developers should verify that:
Only registered tools can execute.
Every argument is validated.
User capabilities are checked.
Resource-level permissions are enforced.
Sensitive operations require approval.
Duplicate operations are prevented.
External requests use approved destinations.
Execution limits are enforced server-side.
Audit events capture important decisions.
Automated tests should cover the complete workflow from tool selection through validation, authorization, execution, and result delivery.
Common Mistakes to Avoid
Allowing arbitrary function execution: Never execute model-generated PHP function names or callbacks. Use a fixed application-controlled tool registry.
Exposing every tool to every AI feature: Provide each assistant with only the operations required for its intended purpose.
Trusting AI-generated arguments: Validate every parameter before passing it to WordPress APIs or database queries.
Checking permissions only in the interface: Enforce authorization inside the server-side tool handler.
Ignoring record-level permissions: A user who can use a tool does not automatically have access to every record.
Allowing sensitive operations without approval: Require appropriate authorization for deleting data, changing prices, publishing content, or sending bulk messages.
Providing unrestricted database access: Use predefined application functions and prepared SQL queries instead of arbitrary model-generated statements.
Allowing arbitrary external URLs: Restrict destinations and validate the information that tools can transmit.
Ignoring repeated execution: Use idempotency controls and execution-state tracking for important operations.
Logging sensitive tool arguments: Record useful audit information without unnecessarily storing private data or credentials.
Best Practices Checklist
Before releasing a WordPress AI plugin with tool execution, verify that:
Every tool has a clearly defined purpose.
Tools are registered in an application-controlled allowlist.
Each AI feature receives only the tools it needs.
Tool arguments are validated against strict schemas.
WordPress capabilities are checked before execution.
Resource-level ownership and permission checks are enforced.
AI tools cannot execute arbitrary PHP functions or SQL statements.
Database operations use predefined queries and $wpdb->prepare() where needed.
Sensitive operations require appropriate authorization and approval.
External requests use controlled destinations.
API credentials remain server-side.
REST and AJAX endpoints enforce authentication and authorization.
Tool-call limits and resource restrictions are applied.
Duplicate and replayed operations are controlled.
Background jobs recheck relevant permissions.
Tool outputs are validated before reuse.
Audit logs capture significant execution events.
Automated tests cover unauthorized and repeated tool calls.
Why Choose Kaddora?
Kaddora focuses on WordPress solutions, AI integration, website functionality, and business workflow automation. Developing reliable AI-powered plugins requires more than connecting a model to application functions. Developers must also understand tool permissions, execution boundaries, data protection, and secure automation architecture.
ThemeKaddora provides WordPress plugins, themes, and templates for developers, agencies, and website owners working on different digital projects. A practical approach to WordPress development and AI security helps developers create useful automation features while maintaining control over website data, application permissions, and sensitive operations.
Conclusion
AI tool abuse is an important security risk for WordPress plugins that allow models to interact with website functionality, databases, external services, and automated workflows.
An AI model may request an unsupported operation, supply manipulated arguments, access resources beyond the user's permissions, or repeatedly trigger a tool. These risks become more serious when tools have excessive privileges or execute sensitive operations without approval.
Preventing tool abuse requires a controlled architecture. Developers should maintain an application-controlled tool registry, validate every argument, enforce WordPress capabilities, verify resource-level permissions, and restrict external requests. Sensitive actions should require explicit approval, while execution limits and idempotency controls help prevent excessive or repeated operations.
Monitoring and automated testing provide additional protection by making unauthorized attempts and unexpected execution patterns easier to identify.
Most importantly, an AI model should never have independent authority to execute WordPress operations. It may request an action, but the application must validate, authorize, and execute it.
By combining restricted tool access, server-side authorization, controlled execution handlers, and continuous monitoring, developers can build secure AI-powered WordPress plugins that support automation without surrendering control over website operations.
Frequently Asked Questions
What is AI tool abuse in WordPress plugins?
AI tool abuse occurs when an AI-powered plugin uses an available function in an unauthorized, unintended, excessive, or unsafe way. It may involve private data retrieval, unauthorized modifications, excessive API requests, or misuse of external services.
Why should WordPress AI plugins use a tool allowlist?
A tool allowlist restricts an AI model to predefined application operations. It prevents the model from selecting arbitrary PHP functions, database commands, or unsupported application actions.
Can AI-generated tool calls be trusted?
No. AI-generated tool calls should be treated as untrusted requests. WordPress must validate their arguments, verify user permissions, check resource ownership, and enforce approval requirements before execution.
How can developers prevent unauthorized AI tool execution?
Developers should use an application-controlled tool registry, capability checks, resource-level authorization, strict argument validation, and controlled execution handlers. Sensitive operations should require explicit approval.
Should AI agents have direct database access in WordPress?
No. AI agents should use narrowly defined application tools that perform approved operations through WordPress APIs or controlled database queries. Arbitrary SQL execution should never be exposed to a model.
How can developers prevent repeated AI tool operations?
Use execution identifiers, persistent operation status, and idempotency controls to prevent duplicate requests. Recheck authorization and approval before processing repeated or retried operations.
Why choose ThemeKaddora?
ThemeKaddora offers WordPress plugins, themes, and templates that help developers, agencies, and website owners find practical digital resources for building, customizing, and extending their online projects.
How can developers test WordPress AI tool abuse prevention?
Developers can test unsupported tool requests, invalid arguments, unauthorized resource access, repeated execution, approval bypass attempts, arbitrary external destinations, and background-job permission changes. Tests should cover the complete tool-execution workflow.
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