Validate a workflow's pipeline definition. Returns structured errors per step. Use this after creating or updating a workflow to check for: - Missing step connections (broken next.stepId references) - Missing required fields (app action without inputs, AI step without prompt) - Unreachable steps ...
Part of the Agentled MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents call validate_workflow to retrieve information from Agentled without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though validate_workflow only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
tools:
validate_workflow:
rules:
- action: allowSee the full Agentled policy for all 56 tools.
Agents calling read-class tools like validate_workflow have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.
Validate a workflow's pipeline definition. Returns structured errors per step. Use this after creating or updating a workflow to check for: - Missing step connections (broken next.stepId references) - Missing required fields (app action without inputs, AI step without prompt) - Unreachable steps (not connected to the trigger chain) - Invalid app/action IDs (not in the app registry) - Missing trigger or milestone steps - List field misconfigurations (missing itemFields, defaultValue format mismatches) - Config page field validation (missing name/type on input page fields) Each error/warning may include a "suggestedFix" with a concrete remediation. You can also pass a pipeline object to validate a draft before saving. Returns: { valid: boolean, errors: [...], warnings: [...], stepCount: number }. It is categorised as a Read tool in the Agentled MCP Server, which means it retrieves data without modifying state.
Add a rule in your Intercept YAML policy under the tools section for validate_workflow. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Agentled MCP server.
validate_workflow is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the validate_workflow rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the Intercept policy for validate_workflow. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
validate_workflow is provided by the Agentled MCP server (@agentled/mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept