Verify a generated output with CHEAP structural signals ($0, no LLM call) and get an escalation verdict — the post-generation half of confidence-gated tier routing (route → generate → verify → escalate on failure). Checks: empty/truncated output, refusal patterns, degenerate repetition, and real ...
AI agents call hooks_model-verify to retrieve information from Ruflo without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool is purely analytical and observational. It examines pre-existing output, performs structural validation checks, and returns analysis results. While it records verdicts to a learning stream, this is metadata logging about model performance rather than writing user data or executing operations. The tool has no side effects beyond internal telemetry.
From the tool's definition Tool performs verification and analysis of generated outputs using 'CHEAP structural signals' and 'no LLM call'. Returns a verdict object with confidence, reasons, and suggestions.
Attacks that exploit this kind of access
Verify a generated output with CHEAP structural signals ($0, no LLM call) and get an escalation verdict — the post-generation half of confidence-gated tier routing (route → generate → verify → escalate on failure). Checks: empty/truncated output, refusal patterns, degenerate repetition, and real syntax parsing for code/JSON tasks (TypeScript compiler / JSON.parse). Returns {confident, reasons[], suggestedTier, suggestedModel, escalate}. By default the verdict is recorded into the model-routing learning stream (success when confident, escalated when not) so the bandit learns which task shapes the cheap tier fails on. Use when you just generated with the tier hooks_model-route picked and must decide accept-vs-escalate BEFORE acting on the output; accepting cheap-tier output unverified is wrong because structurally unusable results (refusals, truncation, unparseable code) silently propagate downstream, and pre-generation routing alone cannot catch them. Not a semantic-quality judge — it only catches structurally unusable outputs. It is categorised as a Read tool in the Ruflo MCP Server, which means it retrieves data without modifying state.
Register the Ruflo MCP server in PolicyLayer and add a rule for hooks_model-verify: 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 Ruflo. Nothing to install.
hooks_model-verify 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 hooks_model-verify 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 hooks_model-verify. 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.
hooks_model-verify is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
hooks_model-verify is one line of Ruflo's registry record.
The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.
Teams ship this data inside their own products. See what a licence covers →