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get_citation_metrics

Retrieve field-normalized citation metrics including relative citation ratio and percentile ranking for PubMed articles to evaluate research impact.

Instructions

Get citation metrics from NIH iCite for articles.

Returns field-normalized citation data including:

  • citation_count: Total number of citations

  • relative_citation_ratio (RCR): Field-normalized metric (1.0 = average)

  • nih_percentile: Percentile ranking (0-100)

  • citations_per_year: Citation velocity

  • apt: Approximate Potential to Translate (clinical relevance 0-1)

Can sort and filter results by citation metrics.

Args: pmids: PubMed IDs - accepts multiple formats: - "12345678,87654321" (comma-separated) - ["12345678", "87654321"] (list) - "PMID:12345678" (with prefix) - "last" to use PMIDs from the last search sort_by: Metric to sort by: - "citation_count": Raw citation count (default) - "relative_citation_ratio": Field-normalized (recommended) - "nih_percentile": Percentile ranking - "citations_per_year": Citation velocity min_citations: Filter out articles with fewer citations min_rcr: Filter out articles with RCR below threshold (e.g., 1.0 = average) min_percentile: Filter out articles below percentile (e.g., 50 = top half)

Returns: Articles with citation metrics, sorted and filtered as requested.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pmidsYes
sort_byNocitation_count
min_citationsNo
min_rcrNo
min_percentileNo
output_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden. It details return fields and parameter behavior but does not explicitly state read-only nature or side effects. However, it implies a query operation (get metrics) and describes output, scoring high but missing explicit safety cues.

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

Conciseness4/5

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

The description is thorough and well-structured with a summary line, bulleted return fields, and parameter explanations. While slightly long, every sentence adds value. It could be more concise but remains clear and organized.

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

Completeness5/5

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

Given the tool's complexity (6 params, 1 required) and the presence of an output schema, the description is complete: it explains return fields, sorting, filtering, and all parameter options. An agent can confidently invoke this tool with the provided information.

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?

Schema coverage is 0%, so description fully compensates by detailing all parameters: pmids formats, sort_by options with explanations, and filter thresholds (min_citations, min_rcr, min_percentile). Even output_format is mentioned via enum in schema. No parameter information is missing.

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 the tool retrieves citation metrics from NIH iCite, listing specific metrics like citation_count, RCR, and nih_percentile. This distinguishes it from sibling tools like find_citing_articles or get_article_details, which have different focuses.

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

Usage Guidelines4/5

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

The description explains sorting and filtering capabilities but does not explicitly state when to use this tool versus alternatives (e.g., fetch_article_details). The clear purpose and parameter details provide implicit context, but no exclusions or when-not guidance are provided.

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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