lookup_nameResolve target name → coords.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| Resolving | No | Array of resolved target coordinates |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare the tool as read-only, open-world, idempotent, and non-destructive, which covers the safety profile. However, the description adds no additional behavioral context, such as what happens when a name is not found, whether multiple results can be returned, or any rate limits. Given the annotations, a low score is warranted because the description does nothing to enrich the behavioral picture.
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, concise sentence: 'Resolve target name → coords.' It is front-loaded with the verb and resource, contains no filler, and is appropriately sized for a simple tool with one parameter.
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 tool is very simple (one parameter, read-only, has output schema), and the annotations are rich, which lowers the burden on the description. However, the description still fails to mention any details about the output format, error handling, or coordinate system, leaving some gaps. It is minimally viable but not comprehensive.
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?
The input schema has zero description coverage for the 'name' parameter. The description's phrase 'target name' adds minimal clarification, effectively restating the parameter name without explaining format, domain, or valid values. The examples in the schema do some work, but the description fails to compensate for the missing parameter documentation.
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 action ('Resolve') and the resource ('target name → coords'), which is specific and unambiguous. However, it does not distinguish this tool from sibling tools like 'resolve_entity' that might perform a similar function, so it falls short of a 5.
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 provides no guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions. The only implied usage is from the description itself, which is minimal. Sibling tools suggest there are competing similar tools, but no differentiation is offered.
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.
Most tools have distinct purposes, but there is some overlap among ask_pipeworx, ask_pipeworx_grounded, and deep_research, all of which query the Pipeworx database with different levels of structure. The detailed descriptions help differentiate them, but the overlap is notable.
All tool names use snake_case consistently, which is good. However, the naming conventions vary: some are descriptive phrases (e.g., ai_visibility_check), others are verb_noun (e.g., list_subscriptions), and some are compound nouns (e.g., entity_profile). Lack of a single pattern reduces consistency slightly.
34 tools is on the higher side for a single server, but it may be justified given the broad scope of Pipeworx data sources. However, the server name 'Mast Nasa' implies a focus on astronomy, yet only a few tools relate to that domain, making the count feel inflated and unfocused.
The tool set is comprehensive for the Pipeworx data platform, covering querying, grounding, entity resolution, comparison, subscriptions, and more. However, for the implied NASA/Mast domain, the surface is severely incomplete with only four astronomy-specific tools, leaving obvious gaps.