list_toolsList ProteinIQ tools available through the public job API.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Tool name or what you want to do, such as "protein protein docking". Results are ranked by relevance. | |
| tag | No | ||
| task | No | Task or task group id, such as docking, protein-protein-docking, structure-prediction, or binder-design. | |
| limit | Yes | ||
| offset | Yes | ||
| category | No |
Changes observed during successful MCP inspections.
Input schema / properties / q / descriptionAdded value: +"Tool name or what you want to do, such as \"protein protein docking\". Results are ranked by relevance."Input schema / properties / taskAdded value: +{
+ "description": "Task or task group id, such as docking, protein-protein-docking, structure-prediction, or binder-design.",
+ "maxLength": 200,
+ "minLength": 1,
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds nothing beyond that — 'available through the public job API' is vague and says nothing about ranking, pagination, or result shape for a mutation-free catalog read.
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 short sentence with no filler and the resource front-loaded. It is efficient, though its brevity shades into under-specification rather than well-targeted concision.
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?
For a six-parameter tool with two required params, no output schema, and no enum guidance, the description should clarify filter semantics and pagination. It omits all of this, so an agent lacks what it needs to drive the query parameters correctly.
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 only 33%: q and task are documented, but tag, category, limit, and offset carry no schema descriptions. The description mentions no parameters at all, so it does not compensate for the gap — an agent cannot tell from either source what 'tag' or 'category' accept.
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?
States a clear verb+resource ('List ProteinIQ tools'), which is unambiguous on its own. However, it never distinguishes itself from the singular sibling get_tool or from the other list_* catalog tools, leaving the agent to infer the scope is a full directory listing.
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?
No when-to-use guidance is given: nothing says when to call this versus get_tool or get_workflow_tool, and nothing explains that the q/tag/task/category parameters turn it into a search/discovery tool rather than a plain enumeration. The agent must guess the intended discovery workflow.
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.