get_journalFetch a journal by DOAJ id.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | DOAJ journal id |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | DOAJ journal ID | |
| url | No | Journal URL | |
| issn | No | ISSN numbers | |
| title | No | Journal title | |
| publisher | No | Publisher name | |
| created_date | No | Creation date |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description confirms it is a read operation, consistent with annotations (readOnlyHint, idempotentHint). However, it adds no additional behavioral context beyond what annotations already provide, such as behavior on missing IDs or rate limits.
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, concise sentence with no extraneous information. It is entirely front-loaded and efficient.
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 fetch-by-id tool with annotations covering safety and an output schema, the description is complete. No additional details are necessary.
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 description coverage is 100% for the single parameter 'id', which is already documented in the schema. The description does not add further meaning or usage examples beyond the schema.
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 'Fetch a journal by DOAJ id' clearly states the action (fetch), the resource (journal), and the unique identifier (DOAJ id). This effectively distinguishes it from siblings like 'get_article' and 'search_journals'.
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 implies using this tool when you have a DOAJ id, but it does not explicitly state when to use it over alternatives like 'search_journals' or 'get_article'. No exclusion criteria or context is provided.
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.