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prtc
by prtc

Get author metrics

get_author_metrics
Read-onlyIdempotent

Retrieve an author's h-index, total citations, paper count, and citation statistics from NASA ADS by name and optional year range for CVs and research impact tracking.

Instructions

Get comprehensive metrics for an author including h-index, total citations, paper count, and citation statistics. Useful for CV preparation and tracking research impact. Note: matches every paper with this author name, so common names may include other people's papers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearsNoOptional year range (e.g., '2020-2025')
authorYesAuthor name (e.g., 'Coelho, P.' or 'Coelho, Paula R. T.')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description then adds a genuinely useful behavioral caveat absent from structured data: name matching sweeps in every paper with that name, so common names may pull in other people's work. It does not describe return shape or how the years filter interacts with the aggregate.

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?

Three tight sentences with the core purpose and returned fields front-loaded, followed by usage context and the important caveat. Little waste, though the CV sentence is mild filler.

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?

No output schema exists, but the description compensates by naming the metric fields returned, and the annotations cover the safety profile. The ambiguity caveat addresses the main risk. Only minor gaps remain around how years filtering affects totals.

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

Parameters3/5

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

Schema description coverage is 100%, with both author and years documented in the schema, so the baseline is 3. The description adds no syntax, format, or default guidance beyond what the schema already states.

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

Purpose4/5

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

Names a specific verb (get), resource (author metrics) and enumerates the returned fields (h-index, total citations, paper count, citation statistics). It is clearly distinct from paper-oriented siblings like get_author_papers and search_papers, though it never explicitly contrasts itself with get_paper_metrics.

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?

Provides implied context ('useful for CV preparation and tracking research impact') but gives no explicit when-to-use condition, prerequisites, or routing to alternatives such as get_author_papers when the user wants the paper list rather than aggregate metrics.

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