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Part of the Loaditout MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents use review_skill to create or modify resources in Loaditout. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call review_skill repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Loaditout.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
tools:
review_skill:
rules:
- action: allow
rate_limit:
max: 30
window: 60See the full Loaditout policy for all 21 tools.
Agents calling write-class tools like review_skill have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
Leave a rating and optional comment for a skill you have used. Returns a confirmation that the review was recorded. Reviews help other agents and humans decide whether to install a skill. Use this after using a skill to share your experience. Do not review skills you have not actually used. Ratings range from 1 (unusable) to 5 (excellent).. It is categorised as a Write tool in the Loaditout MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Add a rule in your Intercept YAML policy under the tools section for review_skill. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Loaditout MCP server.
review_skill is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the review_skill 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 review_skill. 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.
review_skill 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