List timelines (step execution records) for a specific execution. Each timeline represents a step that ran, with its status, output, and metadata. Use this to inspect individual step results, debug failures, or see the execution flow. To debug the actual prompt used for a step in an execution, fi...
Part of the Agentled server.
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AI agents call list_timelines 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 list_timelines 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": {
"list_timelines": {}
}
} See the full Agentled policy for all 119 tools.
These attack patterns abuse exactly the kind of access list_timelines 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.
List timelines (step execution records) for a specific execution. Each timeline represents a step that ran, with its status, output, and metadata. Use this to inspect individual step results, debug failures, or see the execution flow. To debug the actual prompt used for a step in an execution, find that step's timeline here, then call get_timeline and inspect metadata.computedPrompt. get_step only shows the configured prompt template, not the resolved execution prompt.. 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 list_timelines: 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.
list_timelines 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 list_timelines 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 list_timelines. 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.
list_timelines 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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