Ask Helena

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds useful behavioral context: 'May return evidence only' and 'explicit limits.' This goes beyond annotations without contradicting them, though it doesn't detail what the limits or evidence-only responses mean.

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 two sentences, front-loaded with the action verb 'Answer,' and contains no redundant or filler content. Every phrase adds value (scope, sources, citations, limits).

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?

Despite having output schema and annotations, the description leaves significant gaps: parameter semantics are entirely unexplained, 'explicit limits' is vague, and there is no mention of the site parameter (evidence, helena, folklore, all) or history/language options. This is insufficient for a 5-parameter tool with 0% schema description coverage.

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 0%, so the description must compensate for parameter meaning, but it does not. None of the five parameters (site, history, language, request_id, question) are mentioned or explained, leaving the agent to infer semantics solely from names and enums.

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 tool answers questions about Helena Bioinformatics and its products from approved public sources, with specific verb 'answer' and resource 'questions about Helena Bioinformatics'. It distinguishes from sibling by emphasizing citations and explicit limits, but doesn't explicitly name or contrast with search_public_knowledge.

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 implies usage for factual questions requiring citations ('with citations and explicit limits'), but provides no explicit when-to-use vs alternatives or exclusions. The sibling search_public_knowledge is not referenced, so the guidance is only implied, not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds meaningful context about the search scope ('approved public pages') and the nature of results ('source-cited evidence'), enhancing transparency beyond the structured annotations.

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 concise (two sentences), front-loaded with the action verb 'Search,' and every sentence contributes meaning. It is appropriately brief but could be slightly more informative about scope or parameters without becoming verbose.

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 tool has 5 parameters, including the important 'site' enum, and no parameter descriptions, the description is somewhat minimal. However, the presence of an output schema and annotations mitigate the need to explain return values or safety. The description covers the tool's core purpose but leaves the site/filtering and history behavior unexplained.

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 5 parameters with 0% description coverage, and the tool description provides no details about any of them (site, history, language, question, request_id). The description fails to compensate for the schema's lack of field descriptions, leaving parameter semantics entirely to the schema.

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 tool searches 'approved public pages' and returns 'source-cited evidence,' providing a specific verb, resource, and output type. It distinguishes from the sibling 'ask_public_knowledge' by emphasizing search over asking, though it does not explicitly name the alternative.

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 implies usage by defining what it does ('search approved public pages') and its output ('source-cited evidence'). However, it provides no explicit guidance on when to use this tool instead of the sibling 'ask_public_knowledge' and does not mention exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.