Post a 'changes requested' AI-review comment on a PR. The comment is tagged with isAiReview=true so the gate-checker recognises it. Requires 'repo' scope.
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | Review body (Markdown) | |
| repo | Yes | ||
| owner | Yes | ||
| number | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false and destructiveHint=false. The description adds context about the AI tag and gate-checker recognition, but does not fully describe side effects (e.g., creating a review, triggering notifications). Some behavioral context is provided beyond annotations, but not comprehensively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no extraneous information. Every word adds value: purpose, special tag, scope requirement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately explains the tool's core function but does not cover return values or interaction with sibling tools like how it differs from 'gluecron_comment_pr'. Given 4 params and no output schema, more detail on param roles or outcomes would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is low (25%) with only 'body' described. The description does not explain the meaning of 'owner', 'repo', 'number', or 'body' beyond what the schema provides. For a tool with 4 required params, this is insufficient compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool posts a 'changes requested' AI-review comment on a PR, with a specific tag and scope requirement. It distinguishes itself from generic PR comment tools by the special role and vs sibling like 'gluecron_comment_pr'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions required 'repo' scope and implies use for AI-review changes requests. It does not explicitly state when to use vs alternatives, but the name and context differentiate it from generic comments. Sibling tools include 'gluecron_comment_pr', making the distinction clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have near-identical purposes, such as `gluecron_read_file` and `gluecron_repo_read_file` (both read a file from a repo), and `gluecron_explain_repo` and `gluecron_repo_explain_codebase` (both return cached AI explanation). This creates ambiguity despite minor differences in description. While many tools are distinct, the overlapping pairs force an agent to choose between effectively equivalent operations, lowering disambiguation.
All tools use the `gluecron_` prefix followed by a verb_noun pattern (e.g., `acquire_lease`, `create_issue`, `merge_pr`). A few tools like `gluecron_ai_cost_summary` and `gluecron_repo_explain_codebase` deviate slightly but remain readable and predictable. Overall, the naming convention is largely consistent, making it easy to infer tool function from the name.
With 60 tools, the server far exceeds the 25-tool threshold for 'too many' per the guidelines. Although the server covers a broad developer platform (repository management, issues, PRs, workflows, AI features, etc.), the sheer number of tools makes navigation heavy and risks overwhelming both agents and users. A more focused set would improve coherence.
The tool set is remarkably thorough, covering nearly every lifecycle stage for repositories, issues, pull requests, workflows, branches, commits, and AI-assisted features (chat, test generation, release notes, refactoring, voice-to-PR). Essential CRUD operations are present, and advanced operations like leasing, sandbox provisioning, and multi-repo refactoring are included. There are no obvious gaps for the stated purpose of a developer platform.
