assess_change_risk
Before modifying a file or symbol, predict risk level (low/medium/high/critical) with contributing factors and recommended mitigations. Combines blast radius, complexity, git churn, test coverage, and coupling. Use as a quick risk check. For full impact report with affected tests and dependents u...
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What assess_change_risk does on Trace
AI agents call assess_change_risk to retrieve information from Trace without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why assess_change_risk is rated Low
assess_change_risk performs static analysis to predict risk before changes are made. It retrieves and analyzes metadata (blast radius, complexity, git churn, test coverage, coupling) and returns a risk assessment report. No code is executed, no files are modified, and no side effects occur. This is purely a data retrieval and analysis tool, fitting the Read category (queries data with no side effects).
From the tool's definition Tool description explicitly states 'Read-only' and 'predict risk level' — it analyzes and returns risk assessment data without modifying any code or state.
Attacks that exploit this kind of access
The rule that runs assess_change_risk safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Trace, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For assess_change_risk, this is the rule to start with:
assess_change_risk is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Trace, apply this rule, and every assess_change_risk call is checked against it from then on.
Questions about assess_change_risk
Before modifying a file or symbol, predict risk level (low/medium/high/critical) with contributing factors and recommended mitigations. Combines blast radius, complexity, git churn, test coverage, and coupling. Use as a quick risk check. For full impact report with affected tests and dependents use get_change_impact instead. Read-only. Returns JSON: { risk, level, factors: [{ name, value }], mitigations }. It is categorised as a Read tool in the Trace MCP Server, which means it retrieves data without modifying state.
Register the Trace MCP server in PolicyLayer and add a rule for assess_change_risk: 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 Trace. Nothing to install.
assess_change_risk 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 assess_change_risk 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 assess_change_risk. 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.
assess_change_risk is provided by the Trace MCP server (nikolai-vysotskyi/trace-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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