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Ebi Ols

by io.github.pipeworx-io

List Ontologies

list_ontologies
Read-onlyIdempotent

EMBL-EBI Ontology Lookup Service (OLS4) — page through every biomedical ontology loaded into OLS, such as GO, EFO, MONDO, ChEBI, HPO and UBERON. Returns each ontology's id, title, description, term count, version and status, with size/page controls. Answers which biomedical ontologies are searchable here and what the short id for one is.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo0-based page (default 0).
sizeNo1-500 (default 20).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context: it returns specific fields, supports pagination (size/page controls), and answers the practical question of discovering searchable ontologies and their short IDs. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action ('page through every biomedical ontology'), and every clause provides value. The second sentence clarifies the return fields and purpose without redundancy. No fluff or excessive detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 optional params, output schema exists), the description is complete. It explains what the tool does, the scope (all ontologies in OLS), the fields returned, and the practical use case (finding short IDs). With rich annotations and an output schema, there are no major gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description mentions 'size/page controls' which maps to the 'page' and 'size' parameters, but does not add any new meaning beyond what the schema already provides (defaults, range). The schema's descriptions are sufficient, so no additional semantics are needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool pages through every biomedical ontology in OLS, naming specific ontologies (GO, EFO, MONDO, etc.) and listing returned fields (id, title, description, term count, version, status). It distinguishes itself from siblings like get_ontology and get_term by explicitly focusing on listing all ontologies rather than fetching a single one.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: to browse or enumerate all ontologies and find short IDs. It provides context (OLS4, biomedical ontologies) but does not explicitly name alternatives or exclusions like 'use get_ontology for details of a single ontology.' Thus clear context but no explicit when-not guidance.

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

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TDQS

B3.3/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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.

Tool Count3/5

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.

Completeness2/5

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.

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