get_corpus_summaryReturn public corpus coverage, source, freshness, and count metadata. Results are for literature discovery and professional review, not diagnosis or treatment.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| scope | Yes | ||
| counts | Yes | ||
| sources | Yes | ||
| generated_at | Yes | ||
| contract_version | Yes | ||
| deduplication_keys | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the essential behavioral traits. The description adds only the purpose caveat, not new behavioral context like return format or rate limits. Since annotations are strong, a neutral score 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?
Two short sentences with no filler. The main action and metadata list are front-loaded, and the use-case caveat is a single clause. Every word 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?
With no parameters and an output schema present, the description sufficiently conveys what the tool does, what it returns, and its intended use. Nothing needed for correct invocation or interpretation is missing.
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 tool has zero parameters, so the description has nothing to add. Per the rubric, 0 params earns a baseline of 4. The description correctly omits any parameter details since none exist.
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?
Clear verb 'Return' plus specific resource 'corpus summary' and the exact metadata types (coverage, source, freshness, count). It clearly distinguishes itself from siblings which are about individual publications/works, and includes the intended use case in the second sentence.
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?
Provides the general purpose ('literature discovery and professional review') and a restriction ('not diagnosis or treatment'), but does not explicitly contrast with sibling tools or state when to choose this over get_publication_details or search_biomedical_literature. The usage context is implied by the resource, but not explicit exclusions are given.
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 search and corpus tools are clearly distinct, and the two detail and two neighborhood tools are parallel but differentiated by identifier type (PMID vs. Noodle work ID). The main ambiguity is that get_publication_details and get_work_details both retrieve full records, so agents must understand which identifier they have. support_helena is unrelated but unambiguously separated.
Most tools follow a consistent snake_case get_<resource>_<scope> pattern, and search_biomedical_literature fits the retrieval theme. support_helena is a minor outlier because it uses a different action verb and target, but it does not break the overall naming style.
Seven tools is well-scoped for a read-only literature discovery server: corpus summary, semantic search, two lookup modes, two neighborhood exploration modes, and one support action. The count feels intentional and each tool serves a distinct part of the discovery workflow.
The read-only discovery surface is largely complete with corpus metadata, search, detailed record retrieval, and neighborhood exploration. A minor gap is that direct retrieval is only by PMID or Noodle work ID, not by DOI/PMCID, though search can serve as a workaround.