get_termQuickGO (EBI) — get a single Gene Ontology (GO) term by id. Returns its name, aspect (biological_process|molecular_function|cellular_component), definition, synonyms, and obsolete flag. Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | A GO id, e.g. "GO:0006915". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds that it is keyless (no auth) and specifies the exact return fields, providing useful context beyond 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?
Two concise sentences with no redundant information. Efficiently communicates source, action, return content, and access requirement (keyless).
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 simple lookup tool with one parameter and clear return fields listed, the description is complete. Annotations cover safety, and no output schema is needed given the description of return fields.
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 a clear description for the only parameter 'id'. The description does not add additional meaning beyond what the schema already provides, so baseline 3 is appropriate.
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 what the tool does: get a single GO term by ID, and lists the return fields. It distinguishes from siblings like search_terms by specifying single term lookup.
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?
No explicit when-to-use or alternatives are given, but the purpose is obvious from the description and name. Implied usage for retrieving a specific GO term by ID.
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.
While many tools target distinct resources, there is notable overlap between ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and between discovery tools (discover_tools vs suggest_questions). The Polymarket prediction tools also have blurred boundaries (polymarket_edges, polymarket_edge_tracker, polymarket_arbitrage). This overlap can confuse an agent trying to select the right tool.
Tool names consistently use snake_case and are mostly descriptive. However, naming patterns vary: some start with verbs (list_subscriptions, validate_claim), others with nouns (ask_pipeworx, bet_research). The memory tools use single-word imperatives (remember, recall, forget), which differ from the multi-word pattern. Overall, it's readable but not rigidly consistent.
34 tools is on the high side for a single server, but the breadth of domains (data access, prediction markets, biotech, subscriptions) justifies the count. Some tools feel peripheral (gene_annotations, generate_llms_txt) and could be split off, making the set slightly bloated for the core purpose of business/financial data and prediction markets.
The tool surface covers a wide range of data sources (SEC, FDA, FRED, patents, news) and prediction market analysis comprehensively. However, there are minor gaps: no direct web search tool, no tool for fetching a specific SEC filing by accession (though ask_pipeworx may cover it). The set supports most core workflows without dead ends.