Get allowed fields and minimal JSON examples for pipeline steps. Unknown fields are automatically stripped on save — only fields listed here are persisted. Params - stepType (optional): filter to one of trigger, aiAction, aiActionWithTools, appAction, agentOrchestrator, code, knowledgeSync, share...
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AI agents call get_step_schema 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 get_step_schema 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.
{
"version": "1",
"default": "deny",
"tools": {
"get_step_schema": {}
}
}See the full Agentled policy for all 119 tools.
These attack patterns abuse exactly the kind of access get_step_schema gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Get allowed fields and minimal JSON examples for pipeline steps. Unknown fields are automatically stripped on save — only fields listed here are persisted. Params - stepType (optional): filter to one of trigger, aiAction, aiActionWithTools, appAction, agentOrchestrator, code, knowledgeSync, share, return, milestone, etc. Omit for the full schema. - shape (optional): minimal JSON example for a specific shape. Requires stepType. Examples: - aiAction shapes: standard, report (with Config renderer), email (composed email with approval). - aiActionWithTools shapes: standard, agentic-search (web_search + workspace_memory). - agentOrchestrator shapes: supervisor (Agent Team preset). - share shapes: public (public URL for a report step). - knowledgeSync shapes: standard (deterministic KG field mapping). - outputPage shapes: standard — workflow-level output page schema for context.outputPages (NOT a pipeline step; edit via update_workflow_context). - inputPage shapes: standard — workflow-level configuration input page schema for context.inputPages. Response shape { "description": "...", // schema description "fieldCount": <number>, // total fields (scoped to stepType when provided) "groups": [<field groups>], // schema groups (scoped to stepType when provided) "shapes": [<shape examples>] // only when stepType is set } Top-level keys are backward-compatible with pre-v0.11 callers that read description/groups directly. When to call - Before adding a report step: get_step_schema({ stepType: "aiAction", shape: "report" }). - Before adding a composed-email step: get_step_schema({ stepType: "aiAction", shape: "email" }) — remember to also add an outreachProfile input page. - Before adding an Agent Team: get_step_schema({ stepType: "agentOrchestrator", shape: "supervisor" }). - Before adding an aiActionWithTools step: get_step_schema({ stepType: "aiActionWithTools" }), then agentled tools builtins for the closed builtinType list. - Before adding a code step: get_step_schema({ stepType: "code", shape: "standard" }). Note: only JavaScript is supported — Python will fail at runtime. - Before writing to context.outputPages: get_step_schema({ stepType: "outputPage", shape: "standard" }). Required fields: id, title, pathname, outputSteps[] — missing any crashes the workflow detail UI on load. - Before writing to context.inputPages: get_step_schema({ stepType: "inputPage", shape: "standard" }). Saved values land at sibling context.<contextKey>. Trigger type guidance Prefer schedule (polling) for email intake, document processing, and any workflow where sub-minute latency is not required. Use app_event or webhook only when the user explicitly requires real-time delivery (e.g. "as soon as", "within 30 seconds"). When in doubt, schedule wins — it is idempotent, supports backfill, and needs no event infrastructure.. It is categorised as a Read tool in the Agentled MCP Server, which means it retrieves data without modifying state.
Register the Agentled MCP server in PolicyLayer and add a rule for get_step_schema: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Agentled. Nothing to install.
get_step_schema 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 get_step_schema rule in your PolicyLayer 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 PolicyLayer policy for get_step_schema. 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.
get_step_schema is provided by the Agentled MCP server (@agentled/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 119 Agentled tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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