bug_impact_scan
Given a bug (by ticket, or an ad-hoc title/description), rank the existing features most likely affected, by keyword overlap and shared product. Use it when logging a bug to spot regressions and linkage candidates.
This record as markdown: /tools/ai-featureboard-featureboard/bug-impact-scan.md
What bug_impact_scan does on FeatureBoard
AI agents call bug_impact_scan to retrieve information from FeatureBoard without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why bug_impact_scan is rated Low
bug_impact_scan retrieves and analyzes existing feature data to identify potential relationships and regressions. It has no side effects: it does not create, modify, delete, or execute external operations. The tool is purely informational, designed to assist decision-making by surfacing relevant data correlations.
From the tool's definition Tool performs analysis and ranking of existing features based on keyword overlap and shared product metadata. Description uses 'rank', 'spot', and 'candidates' — all read-only operations that query and correlate data without modifying state.
Attacks that exploit this kind of access
The rule that runs bug_impact_scan safely
PolicyLayer is an MCP gateway: it sits between your AI agents and FeatureBoard, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For bug_impact_scan, this is the rule to start with:
bug_impact_scan 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 FeatureBoard, apply this rule, and every bug_impact_scan call is checked against it from then on.
Questions about bug_impact_scan
Given a bug (by ticket, or an ad-hoc title/description), rank the existing features most likely affected, by keyword overlap and shared product. Use it when logging a bug to spot regressions and linkage candidates. It is categorised as a Read tool in the FeatureBoard MCP Server, which means it retrieves data without modifying state.
Register the FeatureBoard MCP server in PolicyLayer and add a rule for bug_impact_scan: 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 FeatureBoard. Nothing to install.
bug_impact_scan 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 bug_impact_scan 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 bug_impact_scan. 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.
bug_impact_scan is provided by the FeatureBoard MCP server (https://github.com/valentil/featureboard-mcp/releases/download/v0.7/featureboard.plugin). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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