get_articleFetch an article by DOAJ id.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | DOAJ article id |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | DOAJ article ID | |
| url | No | Article URL | |
| year | No | Publication year | |
| title | No | Article title | |
| author | No | List of authors | |
| journal | No | Journal title | |
| abstract | No | Article abstract | |
| created_date | No | Creation date |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral context beyond what annotations already provide. Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description does not contradict these, but it also does not elaborate on traits like rate limits or data freshness. With strong annotations, a score of 3 is appropriate.
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 with no wasted words. It is front-loaded and efficient, conveying the entire purpose in 6 words.
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 tool with one parameter, an output schema, and comprehensive annotations, the description is adequate. It could briefly mention the output format, but the output schema already covers that. Overall, it is complete enough for an agent to use correctly.
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 single parameter 'id' described as 'DOAJ article id'. The description does not add additional meaning beyond what the schema provides. Baseline 3 is correct.
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 'Fetch an article by DOAJ id.' It uses a specific verb ('Fetch') and resource ('article'), and the distinct parameter (DOAJ id) helps differentiate it from sibling tools like 'get_journal' and 'search_articles'.
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 guidance is provided on when to use this tool versus alternatives like 'search_articles' or 'get_journal'. The description does not mention any prerequisites, exclusions, or contextual hints.
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.
Several tool clusters have overlapping purposes: the three ask_pipeworx variants are nearly identical, polymarket_edges and polymarket_arbitrage both scan for opportunities, and ai_visibility_check vs scan_competitor_ai_presence create confusion. Although descriptions are detailed, an agent could easily misselect among these.
Most tools follow snake_case verb_noun (get_article, search_journals, resolve_entity), but there are brand-prefixed names (ask_pipeworx*, pipeworx_trending, pipeworx_feedback) and noun-phrase tools (entity_profile, bet_research) that break the pattern. The three ask_pipeworx variants are consistently named but confusable.
35 tools is excessive for a coherent server, especially one where many tools are meta-routes (ask_pipeworx, deep_research) that could consolidate functionality. The count exceeds the 25-tool threshold for 'heavy' and includes several one-off tools (generate_llms_txt, scan_dependency) that don't fit the dominant data-access theme.
The DOAJ subset is complete for read-only search and retrieval, but the server lacks a clear domain: it mixes DOAJ, prediction markets, memory, and subscriptions. For the broader Pipeworx platform, there are some dead ends (e.g., no subscription editing, no raw historical market data, no batch tools), and the non-DOAJ tools create confusion about what the server is actually for.