searchSearch EOL for a name (common or scientific).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 1-50 (default 10) | |
| query | Yes | e.g. "Panthera leo" or "blue whale" |
| Name | Required | Description | Default |
|---|---|---|---|
| results | Yes | Search results matching the query |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, establishing a safe, non-destructive profile. The description adds no further behavioral details (e.g., pagination, result limits), but does not contradict 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 a single, concise sentence that front-loads the action and resource. It is appropriately short given the tool's simplicity and the thoroughness of other structured fields.
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 has an output schema (not shown), reducing the need to describe return values. However, the description does not mention the scope or nature of results, leaving some ambiguity for a search operation.
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 100% with clear descriptions for both 'query' and 'limit'. The description adds contextual value by specifying 'name (common or scientific)', but does not enhance parameter understanding beyond 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 verb 'Search' and the resource 'EOL' with the specific domain of names (common or scientific). It avoids tautology and provides a concise purpose, though it does not differentiate from siblings like 'search_within' or 'pages_by_name'.
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 gives no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or context for choosing this over other search-related sibling tools.
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, with detailed descriptions that eliminate ambiguity. Even similar tools like ask_pipeworx, ask_pipeworx_grounded, and deep_research are well-differentiated by use case (casual, high-stakes, multi-faceted). The Polymarket and EOL tool suites are internally distinct.
Naming mostly follows snake_case with verb_noun or prefix patterns, but there is inconsistency: e.g., 'ask_pipeworx' vs 'bet_research' vs 'deep_research'. The Polymarket and memory tool groups are internally consistent, but overall the server mixes conventions across sub-domains.
34 tools is on the high side, but the server covers multiple domains (EOL taxonomy, Pipeworx data, Polymarket betting, memory, subscriptions). The count is borderline excessive for a focused server; meta-tools like discover_tools and suggest_questions help, but the sheer number can overwhelm an agent.
The tool set covers many data sources and analysis tasks well, but the server name 'Eol' implies a biological taxonomy focus, which is underserved (only 4 tools). For the broader implicit purpose of a research assistant, there are notable gaps like open-web search, image analysis, or document management.