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scan_pubmed_alerts

Scan PubMed daily for recent papers matching your query and insert results into news briefs for easy review.

Instructions

Scan PubMed for recent papers matching a query.

Uses NCBI E-utilities (free, no API key required). Results are inserted
into news_briefs with source_type='article'. Safe to call daily from the
morning scan scheduler job.

Args:
    query: PubMed search query. Defaults to the query in user-preferences.json
           (pubmed_query field), then to your configured research field from
           user-config.yaml, then to a generic global-health fallback.
    reldate: Look back this many days (default: 1 = yesterday + today).
    max_results: Maximum papers to retrieve (default: 15).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
reldateNo
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description shoulders the burden. It discloses the use of NCBI E-utilities, insertion into news_briefs, and default hierarchy, but lacks details on rate limits, error handling, or what happens if the query fails.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (about 8 lines), well-structured with a clear purpose statement, NCBI note, storage location, scheduling advice, and parameter list. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (3 optional params, no required, output schema exists), the description covers usage, side effects, and parameters well. Minor gaps like response format are likely covered by the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the tool description provides thorough explanations for all three parameters (query, reldate, max_results) including their defaults and fallback logic, adding significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Scan PubMed for recent papers matching a query' and specifies the outcome ('Results are inserted into news_briefs'), which distinguishes it from sibling tools like scan_literature or scan_openalex.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

While it mentions 'Safe to call daily from the morning scan scheduler job' and 'no API key required', it does not explicitly contrast with alternatives (e.g., when to use scan_openalex instead) or state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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