Get the full abstract and metadata of an MMWR article by PubMed ID.
Returns the complete abstract, authors, publication date, volume/issue,
and any MeSH subject headings. Use PMIDs from search_mmwr or
get_recent_reports results.
Args:
pmid: PubMed ID of the MMWR article (e.g. '38271059').
| Name | Required | Description | Default |
|---|---|---|---|
| pmid | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explicitly states the return content (abstract, authors, date, volume/issue, MeSH headings), making the behavior transparent. It does not disclose error handling or rate limits, but these are not critical for a simple read-by-ID operation.
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 compact and well-structured: a clear opening sentence, a concise list of return fields, usage guidance, and a single-parameter Args block. Every sentence earns its place with no redundancy.
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 1-parameter read tool with an output schema, the description fully covers what the tool does, how to use it, and where the input comes from. It does not need to explain return structure since the output schema exists, making this 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 description coverage is 0%, so the description must explain the parameter. It provides an 'Args' section defining 'pmid' as 'PubMed ID of the MMWR article' with an example, adding valuable meaning beyond the bare schema type.
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 clearly identifies the resource: 'full abstract and metadata of an MMWR article by PubMed ID.' This distinguishes it from sibling tools like search_mmwr or get_recent_reports, which focus on finding articles rather than retrieving details for a known PMID.
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 'Use PMIDs from search_mmwr or get_recent_reports results,' providing clear context on when this tool is appropriate. It does not explicitly mention when not to use it or alternatives, but the guidance is sufficient for typical retrieval workflows.
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.
The four tools have distinct purposes: search_mmwr finds articles by topic, get_recent_reports lists latest reports, get_report_detail fetches a specific article's details, and get_disease_surveillance specializes in surveillance data for a disease. There is slight overlap between get_disease_surveillance and search_mmwr, but the descriptions clarify that the former is disease-specific and returns surveillance data.
The naming pattern is mostly consistent with get_ prefix for retrieval actions (get_recent_reports, get_report_detail, get_disease_surveillance) and search_mmwr for search. The suffixes vary (reports, detail, surveillance), which is acceptable but not perfectly uniform.
With only 4 tools, the server is well-scoped for its purpose of providing MMWR report access. Each tool earns its place: search, recent list, detail retrieval, and disease-specific surveillance. No redundancy or excess.
The set covers the core workflow for MMWR reports: search, list recent, and get details. It also adds a specialized disease surveillance tool. A minor gap is the lack of full-text access, but abstract and metadata are sufficient for most use cases.