Report the outcome of using a skill, generating a verifiable execution proof. Returns a JSON object with proof_id, verify_url, and shareable_text. The proof is permanently recorded and contributes to the skill's quality score. Use this after every skill invocation to build your agent's trust scor...
Bulk/mass operation — affects multiple targets
Part of the Loaditout MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents may call report_skill_usage to permanently remove or destroy resources in Loaditout. Without a policy, an autonomous agent could delete critical data in a loop with no way to undo the damage. Intercept blocks destructive tools by default and requires explicit human approval before enabling them.
Without a policy, an AI agent could call report_skill_usage in a loop, permanently destroying resources in Loaditout. There is no undo for destructive operations. Intercept blocks this tool by default and only allows it when a human explicitly approves the action.
Destructive tools permanently remove data. Block by default. Only enable with explicit approval workflows.
tools:
report_skill_usage:
rules:
- action: deny
reason: "Blocked by default — enable with approval"See the full Loaditout policy for all 21 tools.
Agents calling destructive-class tools like report_skill_usage have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Destructive risk category across the catalogue. The same policy patterns (deny, require_approval) apply to each.
report_skill_usage is one of the critical-risk operations in Loaditout. For the full severity-focused view — only the critical-risk tools with their recommended policies — see the breakdown for this server, or browse all critical-risk tools across every MCP server.
Report the outcome of using a skill, generating a verifiable execution proof. Returns a JSON object with proof_id, verify_url, and shareable_text. The proof is permanently recorded and contributes to the skill's quality score. Use this after every skill invocation to build your agent's trust score and help the community identify reliable tools. Do not call this before actually using the skill. Requires the skill slug and a status indicating the outcome.. It is categorised as a Destructive tool in the Loaditout MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Add a rule in your Intercept YAML policy under the tools section for report_skill_usage. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Loaditout MCP server.
report_skill_usage is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the report_skill_usage rule in your Intercept 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 Intercept policy for report_skill_usage. 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.
report_skill_usage is provided by the Loaditout MCP server (loaditout-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept