Validate all AI_README.md files in a project. Checks token count, structure, and content quality. Returns validation results with suggestions for improvement.
AI agents call validate_ai_readmes to retrieve information from Ai Readme without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
config | object | — | Custom validation configuration (optional, uses defaults if not provided) |
projectRoot | string | Yes | The root directory of the project. Use the current working directory (e.g., from environment or pwd). If unsure, pass the project root path. |
excludePatterns | array | — | Glob patterns to exclude (e.g., ["node_modules/**", ".git/**"]) |
Parameters from the server's own tool schema.
This tool only reads and analyzes AI_README.md files to validate their structure, token count, and content quality. It generates informational validation results and suggestions without modifying data, executing external operations, or causing irreversible changes. This is a pure Read operation with minimal risk.
From the tool's definition Tool performs validation and checking operations ('Validate', 'Checks token count, structure, and content quality') with no indication of modifications or destructive actions. It 'Returns validation results' which is pure information retrieval.
Risk signalsHigh parameter count (14 properties)
Documented attack patterns abuse exactly the kind of access validate_ai_readmes gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ai Readme, and nothing reaches the server without passing your rules. This is the rule we recommend for validate_ai_readmes:
{
"version": "1",
"default": "deny",
"tools": {
"validate_ai_readmes": {}
}
}validate_ai_readmes is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Validate all AI_README.md files in a project. Checks token count, structure, and content quality. Returns validation results with suggestions for improvement. It is categorised as a Read tool in the Ai Readme MCP Server, which means it retrieves data without modifying state.
validate_ai_readmes accepts 3 parameters: config, projectRoot, excludePatterns. Required: projectRoot. The full parameter table on this page comes from the server's own tool schema.
Register the Ai Readme MCP server in PolicyLayer and add a rule for validate_ai_readmes: 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 Ai Readme. Nothing to install.
validate_ai_readmes 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 validate_ai_readmes 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 validate_ai_readmes. 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.
validate_ai_readmes is provided by the Ai Readme MCP server (ai-readme-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Ai Readme, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
6 Ai Readme tools catalogued and risk-classified — across an index of 43,000+ MCP servers.