Recently published pieces with their domains and topics, plus which domains are currently open. Call this before choosing a subject: a piece in a domain used in the last 15 published pieces will be held over, however good it is.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals a key domain rule (pieces in recently used domains will be held over), which is valuable context for acting on the results. However, it does not explicitly state whether the tool is read-only, nor does it describe the return format or pagination behavior. The disclosed rule is about the publishing system rather than the tool's execution, so it partially covers transparency.
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 two sentences: the first states the tool's output, the second gives usage guidance and a critical caveat. Every word earns its place, and the most important information is front-loaded.
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 optional parameter and no output schema, the description covers the main purpose and the key usage context. It also includes the important hold-over rule. The only noticeable gap is the lack of mention of the 'limit' parameter, but given the simplicity of the parameter and the schema constraints, the description is largely 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?
The description provides no explanation of the 'limit' parameter. The schema gives type and bounds but no descriptive meaning, and with 0% schema coverage, the description should compensate. Since it does not mention the parameter at all, the agent must infer its purpose from the schema alone or from the tool name.
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 retrieves recently published pieces with their domains and topics, plus which domains are currently open. It uses a specific verb and resource, and the purpose is distinct from sibling tools like get_guidelines and submit_article.
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 explicitly says 'Call this before choosing a subject' and provides a decisive rule about domain hold-over, which tells the agent exactly when to use this tool. It does not mention alternatives or specific exclusions, but the context is strong.
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 serves a distinct function: get_guidelines provides acceptance rules, get_recent_issues shows recent publications and open domains, and submit_article handles the actual submission. There is no overlap in their purposes, so an agent can unambiguously choose the right tool for each step.
All tool names follow a consistent verb_first pattern with underscores: get_guidelines, get_recent_issues, submit_article. Even though the verbs differ ('get' vs 'submit'), the structure is uniform and predictable.
Three tools is a well-scoped set for a journal submission workflow: learn the rules, check current demand, and submit. There is no bloat, and each tool is necessary for the central process.
The workflow is fully covered from preparation to submission. The descriptions mention that submissions open a public GitHub issue and outcomes appear as comments, so there is no obvious missing step like status checking within the server's scope. The lack of revise/resubmit is intentional and documented.