get_articleGet the full metadata and abstract for a single eLife article by its id (e.g. "107545"). Returns title, DOI, type, publication date, authors, abstract, and subjects. Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | eLife article id, e.g. "107545". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds that it returns specific fields and mentions 'Keyless' (likely no authentication required), adding value beyond annotations. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The purpose is front-loaded, followed by return fields and a note about keyless access. Every sentence 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?
No output schema exists, so the description compensates by listing return fields (title, DOI, type, etc.). It does not mention error conditions or format, but for a simple read tool with comprehensive annotations, this is reasonably complete.
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%, so the schema already documents the single 'id' parameter. The description adds an example value but no additional semantics beyond the schema. Baseline score of 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 uses a specific verb ('Get') and resource ('article metadata and abstract'), specifies the identifier format with an example, and lists return fields. It clearly distinguishes from sibling tools like 'search_articles' (search) and 'latest_articles' (list).
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 implicitly indicates usage when you have a specific article id, and provides an example. However, it lacks explicit guidance on when not to use this tool versus alternatives, which would be helpful given the number of 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. Tools like ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are differentiated by reliability mode; entity_profile vs compare_entities serve single vs multi-entity; and memorization, subscription, and search tools occupy separate operational niches. No two tools could be easily confused.
Tool names follow no consistent pattern. Some use verb_noun (ask_pipeworx, resolve_entity, validate_claim), others are noun phrases (polymarket_arbitrage, ai_visibility_check), and some mix verb+noun with underscores inconsistently (generate_llms_txt, scan_competitor_ai_presence). This lack of uniformity makes the surface harder to navigate.
34 tools is borderline high. The server spans multiple domains (data query, prediction markets, eLife, memory, subscriptions), and each domain gets several tools, making the overall surface feel bloated. While individual tools are justified, the total count strains discoverability and hints at scope creep.
The tool set is incomplete relative to its stated breadth. For a server named 'Elife', only 3 tools actually serve eLife; the rest are dominated by Pipeworx and Polymarket. Within the query/data domain, coverage is deep but lacks write/modify tools. Prediction market analysis lacks execution tools (no order placement). This leaves clear gaps for agents that need to act on the data.