Mark beliefs as stale after file changes (Flow ④ doc-refresh). Given changed files, finds related beliefs and marks their status as 'stale' so the next verify_beliefs pass will flag them for re-compilation. Args: changed_files: Comma-separated list of changed file paths
AI agents use refresh_beliefs to create or update resources in Entroly Context Engine — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Entroly Context Engine environment.
This tool modifies the status of existing belief records (marking them as 'stale'), which is a reversible state change. It does not delete data, execute code, or have financial implications. The severity is medium because misuse could invalidate correct beliefs and disrupt the AI agent's context engine, potentially causing cascading re-compilations or degraded performance.
From the tool's definition Mark beliefs as stale after file changes... marks their status as 'stale' so the next verify_beliefs pass will flag them for re-compilation
Documented attack patterns abuse exactly the kind of access refresh_beliefs gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Entroly Context Engine, and nothing reaches the server without passing your rules. This is the rule we recommend for refresh_beliefs:
{
"version": "1",
"default": "deny",
"tools": {
"refresh_beliefs": {
"limits": [
{
"counter": "refresh_beliefs_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}refresh_beliefs stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Mark beliefs as stale after file changes (Flow ④ doc-refresh). Given changed files, finds related beliefs and marks their status as 'stale' so the next verify_beliefs pass will flag them for re-compilation. Args: changed_files: Comma-separated list of changed file paths. It is categorised as a Write tool in the Entroly Context Engine MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Entroly Context Engine MCP server in PolicyLayer and add a rule for refresh_beliefs: 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 Entroly Context Engine. Nothing to install.
refresh_beliefs is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the refresh_beliefs 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 refresh_beliefs. 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.
refresh_beliefs is provided by the Entroly Context Engine MCP server (juyterman1000/entroly). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Entroly Context Engine, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
52 Entroly Context Engine tools catalogued and risk-classified — across an index of 43,000+ MCP servers.