Server-side searchable, paginated list of USERS and TEAMS that can be assigned as the owner of an improvement/task in a project — and the canonical source for resolving a person's user_id when @-mentioning them in a document. Returns two arrays — users (with user_id, display_name, email, avatar_u...
Part of the Stable Baseline server.
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AI agents call listAssignablePrincipals to retrieve information from Stable Baseline 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 listAssignablePrincipals 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": {
"listAssignablePrincipals": {}
}
}See the full Stable Baseline policy for all 184 tools.
These attack patterns abuse exactly the kind of access listAssignablePrincipals 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.
Server-side searchable, paginated list of USERS and TEAMS that can be assigned as the owner of an improvement/task in a project — and the canonical source for resolving a person's user_id when @-mentioning them in a document. Returns two arrays — users (with user_id, display_name, email, avatar_url, has_explicit_permission) and teams (with team_id, name, member_count, has_explicit_permission). Sources: project-level grants + workspace members + organization members + members of teams granted access. Use BEFORE: (1) updateImprovement/updateTask when you need an owner_id (kind='user') or owner_team_id (kind='team'); (2) inserting a <!-- REFERENCE: {"type":"user","id":"…","label":"…"} --> mention in document content via createDocument / editDocument / findAndReplaceTextInDocument. Supports q for ILIKE search on names/emails (users) or team names. Pass kind='user' or kind='team' to scope to a single section, or 'all' (default) for both. Pagination via limit (1-100, default 20) + offset.. It is categorised as a Read tool in the Stable Baseline MCP Server, which means it retrieves data without modifying state.
Register the Stable Baseline MCP server in PolicyLayer and add a rule for listAssignablePrincipals: 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 Stable Baseline. Nothing to install.
listAssignablePrincipals 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 listAssignablePrincipals 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 listAssignablePrincipals. 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.
listAssignablePrincipals is provided by the Stable Baseline MCP server (https://api.stablebaseline.io/functions/v1/cloud-serve/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 184 Stable Baseline tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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