search_issuesSearch issues across public GitLab projects by keyword. Returns issue title, state, author, labels, project ID, and direct URL.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results to return (default 10, max 100) | |
| query | Yes | Search query for issue titles and descriptions |
| Name | Required | Description | Default |
|---|---|---|---|
| issues | Yes | Array of issues matching the search query |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, making the safety profile clear. The description adds value by specifying the search scope (public GitLab projects) and the return fields, which eases agent understanding.
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?
A single, well-structured sentence that front-loads the core purpose and includes key return information. No wasted words.
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 annotations cover safety and idempotency, the output schema exists, and the description summarizes return fields, the description is fully adequate for a search tool. It adds necessary scope constraints (public projects) and result details.
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 100% with clear descriptions for both 'query' and 'limit'. The description does not add any parameter-specific details beyond what the schema provides, so a baseline of 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 specifies the verb 'search', the resource 'issues', the scope 'across public GitLab projects', and the method 'by keyword'. It also lists returned fields, clearly differentiating from sibling tools like 'search_projects'.
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 states it searches public GitLab projects, which implies private projects are excluded, but does not explicitly compare to alternatives or provide when-not-to-use guidance. Given the many sibling tools, more explicit guidance would help.
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.
The vast majority of tools are unrelated to GitLab and cover overlapping domains (multiple ask_pipeworx variants, several Polymarket tools, memory tools). Only three GitLab-specific tools exist, and they are distinct from each other, but overall the set is highly heterogeneous and ambiguous.
Tool names use a mix of conventions: some are snake_case (ask_pipeworx, search_issues), some are compound nouns (get_project, list_subscriptions), and a few are single words (forget, recall). There is no consistent pattern, making it harder to predict tool names.
Despite the server name 'Gitlab Public', only 3 out of 34 tools are related to GitLab. The remaining 31 tools are a collection of unrelated services (Pipeworx data retrieval, Polymarket betting, memory, AI visibility). This is a severe mismatch between the server's stated purpose and its tool composition.
For a GitLab public server, essential tools like project creation, deletion, user management, and merge request handling are completely missing. The Pipeworx tools, while numerous, lack a clear cohesive scope and overlap significantly with each other.