execute_saved_view
Run saved ticket, attention or reviewed-work intent against live owned data. Ordinary views return matching tickets and optional group counts. Triage returns the original reader envelope in data, the view and a definition_token. For triage continuation send expected_definition_token; attention us...
This record as markdown: /tools/com-meta-council-decision-intelligence/execute-saved-view.md
What execute_saved_view does on Meta Council
AI agents invoke execute_saved_view to trigger actions in Meta Council. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
limit | integer | — | Page size: ordinary defaults200/max500, attention defaults100/max500, reviewed work defaults20/max50. Omit for the reader's default. |
cursor | string | — | Reviewed-work next_cursor only; never saved in the definition. |
offset | integer | — | How many tickets to skip. Defaults to 0. |
view_id | string | Yes | The view's id, from list_saved_views. |
expected_definition_token | string | — | Required on triage continuation; bind to the preceding saved definition. |
Parameters from the server's own tool schema.
Why execute_saved_view is rated High
execute_saved_view triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs execute_saved_view safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Meta Council, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For execute_saved_view, this is the rule to start with:
execute_saved_view stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Meta Council, apply this rule, and every execute_saved_view call is checked against it from then on.
Questions about execute_saved_view
Run saved ticket, attention or reviewed-work intent against live owned data. Ordinary views return matching tickets and optional group counts. Triage returns the original reader envelope in data, the view and a definition_token. For triage continuation send expected_definition_token; attention uses next_offset, reviewed work uses next_cursor with offset0. A changed definition refuses409: reload and restart. Ordinary views refuse cursor/token. Results are always YOUR tickets: a shared view shares the question, not the answers, so opening a teammate's view runs it against your own work and never reveals theirs. An archived view is refused rather than executed. Returns the same payload the web app receives. Follow next_offset while has_more; live ticket or filter changes can shift offset pages, so restart to refresh. Requires authentication and the tickets:read scope. It is categorised as a Execute tool in the Meta Council MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
execute_saved_view accepts 5 parameters: limit, cursor, offset, view_id, expected_definition_token. Required: view_id. The full parameter table on this page comes from the server's own tool schema.
Register the Meta Council MCP server in PolicyLayer and add a rule for execute_saved_view: 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 Meta Council. Nothing to install.
execute_saved_view is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the execute_saved_view 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 execute_saved_view. 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.
execute_saved_view is provided by the Meta Council MCP server (https://meta-council.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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