gluecron_refactor_across_repos
Plan + execute a refactor that spans multiple repos owned by the caller. Wraps src/lib/multi-repo-refactor.ts. dry_run: true returns the plan only. Requires 'repo' scope.
This record as markdown: /tools/com-gluecron-gluecron/gluecron-refactor-across-repos.md
What gluecron_refactor_across_repos does on Gluecron
AI agents invoke gluecron_refactor_across_repos to trigger actions in Gluecron. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
dry_run | boolean | — | When true, returns the plan and does NOT execute. |
description | string | Yes | Natural-language description |
repository_ids | array | — | Optional explicit repo IDs to scope the refactor to. |
Parameters from the server's own tool schema.
Why gluecron_refactor_across_repos is rated High
This tool executes a refactoring operation across multiple repositories, which is an execute action that modifies multiple codebases. While it creates/modifies code (Write), the critical aspect is that it EXECUTES a refactoring plan across multiple repos, making it Execute-class. It's not Destructive because refactors are typically reversible through git history, and it's not Financial.
From the tool's definition Plan + execute a refactor that spans multiple repos. The tool performs actual code modifications across repositories (when dry_run is false), making it an execution operation that triggers external code transformation operations whose effects depend on the…
Attacks that exploit this kind of access
The rule that runs gluecron_refactor_across_repos safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gluecron, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For gluecron_refactor_across_repos, this is the rule to start with:
gluecron_refactor_across_repos stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Gluecron, apply this rule, and every gluecron_refactor_across_repos call is checked against it from then on.
Questions about gluecron_refactor_across_repos
Plan + execute a refactor that spans multiple repos owned by the caller. Wraps src/lib/multi-repo-refactor.ts. dry_run: true returns the plan only. Requires 'repo' scope. It is categorised as a Execute tool in the Gluecron MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
gluecron_refactor_across_repos accepts 3 parameters: dry_run, description, repository_ids. Required: description. The full parameter table on this page comes from the server's own tool schema.
Register the Gluecron MCP server in PolicyLayer and add a rule for gluecron_refactor_across_repos: 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 Gluecron. Nothing to install.
gluecron_refactor_across_repos is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the gluecron_refactor_across_repos 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 gluecron_refactor_across_repos. 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.
gluecron_refactor_across_repos is provided by the Gluecron MCP server (https://gluecron.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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