export_audit
Unified compliance/traceability export: for one ticket or the whole board, merges the existing audit primitives into a single report \u2014 field-change events (status/priority/label moves), work-log sessions, sub-agent dispatch records, requirements pads with acceptance-criteria state, review co...
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What export_audit does on FeatureBoard
AI agents call export_audit 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 export_audit is rated Low
This tool aggregates and exports existing data into a report — it reads from multiple audit primitives and produces a compliance/traceability export. There are no indications it modifies, deletes, or executes anything.
From the tool's definition 'Unified compliance/traceability export', 'merges the existing audit primitives into a single report', includes field-change events, work-log sessions, review comments, decision-log entries, correlated commits, and drift-harness scores
Attacks that exploit this kind of access
The rule that runs export_audit 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 export_audit, this is the rule to start with:
export_audit 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 export_audit call is checked against it from then on.
Questions about export_audit
Unified compliance/traceability export: for one ticket or the whole board, merges the existing audit primitives into a single report \u2014 field-change events (status/priority/label moves), work-log sessions, sub-agent dispatch records, requirements pads with acceptance-criteria state, review comments with resolution, decision-log entries, correlated commits (recorded-first with git log --grep fallback), and drift-harness scores. Includes a board-level compliance summary: status counts, acceptance coverage, unresolved reviews, work totals, drift flags, and Done tickets with no correlated commit. Formats: json (structured), markdown (human-readable dossier), csv (flat chronological trail rows for BI). Read-only. 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 export_audit: 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.
export_audit 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 export_audit 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 export_audit. 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.
export_audit 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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