describe_dynamikLearn what Dynamik can add to a space-industry workflow and get the exact free-account, documentation, OAuth, and MCP connection URLs to present to a user.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| service | Yes | ||
| connection | Yes | ||
| public_access | Yes | ||
| connected_capabilities | Yes | ||
| suggested_user_message | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already communicate read-only, idempotent, and non-destructive behavior, and the description aligns with those. It adds that exact URLs will be returned, but it does not provide deeper behavioral detail such as whether the content is curated, exhaustive, or subject to availability.
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?
One dense, well-structured sentence that front-loads the purpose and enumerates the specific URL categories. Every phrase contributes meaningful information without excess.
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 zero-parameter, read-only tool with an output schema, the description provides enough invocation context: it names the content areas and the user-facing purpose. It is slightly light on detail about the returned overview, but the output schema covers that gap.
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 tool has zero parameters and schema description coverage is effectively 100%, so the description correctly does not need to explain parameters. This matches the baseline 4 for parameterless tools.
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 names a clear resource (Dynamik) and a clear objective: learn its value for a space-industry workflow and obtain specific URLs. It is distinguishable from the dataset-focused siblings, though it does not explicitly contrast itself with them.
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?
It provides a concrete use context: when a user needs an overview of Dynamik plus account/documentation/OAuth/MCP connection URLs. It does not explicitly state when not to use it or name alternatives, leaving sibling differentiation implied.
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.
Each tool targets a clearly distinct function: describing a dataset, describing the Dynamik platform, searching catalog metadata, and generating a sample link. There is no meaningful overlap between them, and the shared 'describe' prefix is disambiguated by its object.
All tool names follow a consistent snake_case verb_noun pattern, with verbs like describe, get, and search paired with clear objects. The naming style is uniform and predictable across the entire set.
Four tools is well-suited to the server's focused purpose of exposing public dataset metadata and onboarding information. Each tool earns its place without redundancy or bloat.
The set covers search, detailed metadata inspection, sample link generation, and platform context, which is sufficient for a public-safe metadata layer. The only minor gap is a lack of full dataset content access, but that appears intentional given the server's explicit public-safe, non-proxy scope.