support_helenaLearn how an agent can support or spread Helena's free public scientific infrastructure through the separate Helena Good MCP. This is an explicit opt-in information action. It does not initiate payment, create a relay, or change Ask Helena evidence or answers.
| Name | Required | Description | Default |
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No arguments | |||
| Name | Required | Description | Default |
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No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description goes further by clarifying it is an explicit opt-in information action and explicitly lists what it does not do (payment, relay creation, evidence changes). This adds valuable behavioral context beyond annotations, such as the pointer to a separate MCP.
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 extremely concise—two sentences. The purpose is front-loaded, followed by explicit exclusions and side-effect disclaimers. No wasted words; every clause adds value to the agent's understanding.
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?
With no parameters and an output schema present, the description effectively covers all needed context. It explains the tool's role, its limitations, and points to the separate MCP for further details. Nothing essential is missing for an agent to correctly decide to invoke this tool.
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, so the input schema is empty and schema coverage is trivially 100%. Per the baseline for 0 params, a score of 4 is appropriate since no additional parameter documentation is required; the description does not need to elaborate on parameters.
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 states a specific verb and resource: 'Learn how an agent can support or spread Helena's free public scientific infrastructure through the separate Helena Good MCP.' It clearly distinguishes itself from siblings (ask_public_knowledge, search_public_knowledge) by focusing on support rather than knowledge retrieval, and it explicitly frames itself as an information action.
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 clear context for when to use it—when an agent needs to understand how to support or spread Helena's infrastructure. It also states exclusions: it does not initiate payment, create a relay, or change Ask Helena evidence/answers. However, it does not explicitly name alternative tools for other use cases, though siblings are implied to be for knowledge queries.
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 has a clearly distinct purpose: ask_public_knowledge answers questions, search_public_knowledge retrieves cited evidence, and support_helena handles a separate opt-in action about supporting Helena. No overlap or ambiguity between them.
All tools follow a consistent verb_noun pattern: ask_public_knowledge, search_public_knowledge, support_helena. The style is uniform and intuitive, making the set predictable.
Three tools is a well-scoped count for a knowledge-answering server. Each tool earns its place: one for querying, one for searching, and one for a distinct support action. No bloat or thinness.
The server's purpose is to provide answers from public knowledge with citations. The ask and search tools cover the core workflows fully, and the support tool addresses a separate but relevant action. No obvious gaps in the domain.