get_termTerm details. Pass either iri, short_form, or obo_id (the latter two require ontology).
| Name | Required | Description | Default |
|---|---|---|---|
| iri | No | Full term IRI (preferred). | |
| obo_id | No | OBO id, e.g. "EFO:0000408" | |
| ontology | Yes | ||
| short_form | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the bar is lower. The description adds the invocation constraint of passing exactly one identifier, but it does not disclose additional behavioral aspects such as error handling, return format, or edge cases. It is adequate but not rich.
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 sentence that is front-loaded with 'Term details' and provides essential parameter guidance without any wasted words. Every word earns its place.
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 presence of an output schema and comprehensive annotations, the description is largely complete for a simple retrieval tool. It clearly explains how to call the tool, though it omits guidance on when to select this tool over related term tools, leaving a minor contextual 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 description adds meaning beyond the schema by clarifying that the three identifiers are mutually exclusive alternatives and that short_form and obo_id require the ontology parameter. The schema only describes iri and obo_id, so the description compensates for the 50% coverage with important usage constraints.
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 'Term details' clearly indicates the tool retrieves information about a term, but it lacks a specific verb and does not differentiate from sibling tools like term_ancestors or term_children. It is clear but without sibling differentiation, matching a score of 4.
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 parameter selection rules (pass either iri, short_form, or obo_id, with the latter two requiring ontology) but gives no guidance on when to use this tool versus alternatives. There is no mention of exclusions or preferred contexts, so the score is low.
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.
Many tools have overlapping purposes, especially among Pipeworx query tools (ask_pipeworx, ask_pipeworx_grounded), betting research tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_kalshi_spread), and memory tools (remember, recall, forget). An agent could easily select the wrong tool. Additionally, tools like 'discover_tools', 'search', and 'search_within' have unclear boundaries.
Most tool names use snake_case (e.g., 'entity_profile', 'validate_claim'), but there are inconsistencies with single-word verbs like 'forget', 'recall', 'remember', 'subscribe', 'unsubscribe', and the mixed pattern of 'ask_pipeworx' vs 'pipeworx_feedback'. Overall, the naming is somewhat consistent but not fully predictable.
With 32 tools, the server has a high but not extreme count. However, the tools span multiple unrelated domains (ontologies, financial data, betting, memory, subscriptions, AI visibility), making the server feel like a collection of disparate features rather than a focused toolset. This reduces the appropriateness of the count for a single server.
The tool surface has significant gaps. For example, ontology tools lack create/update/delete operations; betting tools only provide research and analysis but no placement; memory tools allow save/recall/delete but not update; and there is no tool for user authentication or account management despite subscription features. The server covers many areas but none completely.