Generate tests for a PR via Claude. Wraps src/lib/ai-test-generator.generateTestsForPr. Mode 'follow-up-pr' opens a new PR; 'append-commit' commits onto the head branch. Requires 'repo' scope.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | 'follow-up-pr' or 'append-commit' | |
| repo | Yes | ||
| owner | Yes | ||
| number | Yes | PR number |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the tool is not read-only (readOnlyHint=false) and not destructive (destructiveHint=false). The description adds that it wraps a function and requires 'repo' scope, but does not disclose additional behaviors such as cost, rate limits, or side effects beyond creating PRs/commits.
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 three sentences, each serving a distinct purpose: stating the main function, explaining modes, and noting scope requirement. No unnecessary words, and the purpose is front-loaded.
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?
Given the tool has 4 parameters and no output schema, the description covers the essential aspects (purpose, modes, scope). However, it could be more complete by explaining what the tool returns (e.g., PR URL or commit SHA) or any asynchronous behavior.
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 description coverage is 50% (mode and number have descriptions; repo and owner do not). The description adds context for the 'mode' parameter and mentions the required scope, but does not fully compensate for the missing schema descriptions. Baseline 3 is appropriate.
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's verb ('Generate tests') and resource ('for a PR'). The two modes are specified, distinguishing it from sibling tools like gluecron_generate_commit_message or gluecron_generate_pr_description, which serve different purposes.
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 explains the two modes ('follow-up-pr' and 'append-commit') and their outcomes, and mentions the required 'repo' scope. However, it does not explicitly state when to use this tool over alternatives or when not to use it, though no direct competing sibling exists.
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.
