Term Ancestors
term_ancestorsTransitive ancestors of a term.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| iri | Yes | ||
| ontology | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| _embedded | No |
term_ancestorsTransitive ancestors of a term.
| Name | Required | Description | Default |
|---|---|---|---|
| iri | Yes | ||
| ontology | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| _embedded | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint and idempotentHint, so the safety profile is clear. The description adds the behavioral detail that the result includes the full transitive closure of ancestors, not just immediate parents, which is not evident from the name or schema. It does not discuss edge cases or error handling, but given the strong annotation coverage, this is acceptable.
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, consisting of only four words. It is front-loaded and contains no redundant or filler content. However, it may be too terse, missing opportunities to elaborate on usage or parameters, but conciseness itself is well-executed.
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's simplicity (two required parameters) and the presence of an output schema (which likely documents return values), the description could be minimal yet sufficient. However, it lacks critical contextual information such as when to use this tool, how the transitive ancestors are computed (e.g., whether self is included), and any domain-specific nuances. The description leaves too much to inference.
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 schema has zero description coverage, so the description must compensate. It only mentions 'a term' without explaining how 'ontology' and 'iri' relate to identifying that term. The parameter names are self-explanatory, and the schema example provides some context, but the description itself fails to add meaningful parameter-level guidance.
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 that the tool returns 'transitive ancestors of a term,' which specifies the resource (term) and the action (returning ancestors). It distinguishes itself from sibling tools like 'term_children' by the word 'transitive,' indicating all ancestors rather than just direct parents. However, the verb is implicit and the term 'transitive' might be ambiguous to non-domain experts.
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?
There is no guidance on when to use this tool versus alternatives. The presence of sibling tools like 'term_children' and 'get_term' suggests potential overlap, but the description does not mention these or provide heuristics for choosing this tool. It lacks any context about exploration of ontology hierarchies or relationships.
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.