report_issue

SERVERAdia Ai SOURCE@adia-ai/mcp

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade C, identity unverified Pull the record →

This record as markdown: /tools/adia-ai-mcp/report-issue.md

WHAT IT DOES

What report_issue does on Adia Ai

AI agents use report_issue to create or update resources in Adia Ai, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Adia Ai environment.

RISK

Why report_issue is rated Medium

An AI agent can call report_issue faster than any human can review: one bad instruction and it creates or modifies resources in Adia Ai by the hundred, each call as confident as the last.

Risk signalsBulk/mass operation — affects multiple targets

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs report_issue safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Adia Ai, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For report_issue, this is the rule to start with:

report_issue Rate-limited

report_issue stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "report_issue": {
      "limits": [
        {
          "counter": "report_issue_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Adia Ai, apply this rule, and every report_issue call is checked against it from then on.

FAQ

Questions about report_issue

What does the report_issue tool do? +

File a structured issue ticket \u2014 writes BOTH a machine-readable JSON file AND a human-readable Markdown report containing the full session trace (intent, retrieval log, LLM prompts, every attempt. It is categorised as a Write tool in the Adia Ai MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on report_issue? +

Register the Adia Ai MCP server in PolicyLayer and add a rule for report_issue: 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 Adia Ai. Nothing to install.

What risk level is report_issue? +

report_issue is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit report_issue? +

Yes. Add a rate_limit block to the report_issue 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.

How do I block report_issue completely? +

Set action: deny in the PolicyLayer policy for report_issue. 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.

What MCP server provides report_issue? +

report_issue is provided by the Adia Ai MCP server (@adia-ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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