This record as markdown: /tools/io-github-aifity-omnigit-mcp/issue-write.md
What issue_write does on GitHub
AI agents use issue_write to create or update resources in GitHub, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GitHub environment.
Why issue_write is rated Medium
This tool creates new GitHub issues or modifies existing ones, which are both reversible operations. Issues can be edited or deleted later, so it does not meet the Destructive threshold. It does not execute arbitrary code (Execute), move money (Financial), or merely read data (Read).
From the tool's definition Tool name 'issue_write' and description 'Create or update issue' indicate reversible creation and modification of GitHub issues.
Attacks that exploit this kind of access
The rule that runs issue_write safely
PolicyLayer is an MCP gateway: it sits between your AI agents and GitHub, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For issue_write, this is the rule to start with:
issue_write 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.
The button opens the PolicyLayer dashboard: create your workspace, connect GitHub, apply this rule, and every issue_write call is checked against it from then on.
Questions about issue_write
Create or update issue. It is categorised as a Write tool in the GitHub MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the GitHub MCP server in PolicyLayer and add a rule for issue_write: 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 GitHub. Nothing to install.
issue_write 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 issue_write 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 issue_write. 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.
issue_write is provided by the GitHub MCP server (oci:ghcr.io/aifity/omnigit-mcp:0.5.0). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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