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Semanticscholar

by io.github.pipeworx-io

Get Author

get_author
Read-onlyIdempotent

Search for academic authors by name on Semantic Scholar. Returns up to 5 matches with affiliations, paper count, total citation count, h-index, and profile URL. Keyless.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesAuthor name to search for, e.g. "Yoshua Bengio".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL to author profile
nameNoAuthor name
papersNoRecent publications (up to 20)
h_indexNoH-index of the author
homepageNoAuthor homepage URL
author_idNoSemantic Scholar author ID
paper_countNoTotal number of papers published
affiliationsNoAuthor affiliations
citation_countNoTotal number of citations

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "author_id": "2190855"
-  }
-]New value: +[
+  {
+    "name": "Yoshua Bengio"
+  }
+]
  2. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "author_id": "2190855"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "affiliations": {
+      "description": "Author affiliations",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "author_id": {
+      "description": "Semantic Scholar author ID",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "citation_count": {
+      "description": "Total number of citations",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "h_index": {
+      "description": "H-index of the author",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "homepage": {
+      "description": "Author homepage URL",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "name": {
+      "description": "Author name",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "paper_count": {
+      "description": "Total number of papers published",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "papers": {
+      "description": "Recent publications (up to 20)",
+      "items": {
+        "properties": {
+          "citation_count": {
+            "description": "Number of citations for this paper",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "paper_id": {
+            "description": "Paper ID",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "title": {
+            "description": "Paper title",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "year": {
+            "description": "Publication year",
+            "type": [
+              "number",
+              "null"
+            ]
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "url": {
+      "description": "URL to author profile",
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "type": "object"
+}
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive, so safety is clear. The description adds value by specifying the limit of 5 matches and the field list, plus the keyless access trait, which are behavioral traits beyond annotations.

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 extremely concise: two sentences front-loading the core purpose and return details, with no superfluous words. Every sentence adds essential information.

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?

With a single parameter and an output schema provided, the description covers the key aspects: search behavior, return fields, limit, and accessibility. It is complete for the tool's simplicity, though it could hint at the nature of the search (e.g., fuzzy matching).

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 coverage is 100% with a well-described 'name' parameter including an example. The description does not add additional parameter meaning beyond this baseline, so a score of 3 is appropriate.

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?

Description clearly states the action (search), target (academic authors), source (Semantic Scholar), and expected output (up to 5 matches with affiliations, paper count, etc.). It distinguishes from siblings like 'search_papers' by focusing on authors.

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 mentions 'Keyless', indicating no API key is needed, which is a usage prerequisite. However, it does not explicitly state when to use this tool over alternatives (e.g., for author lookup vs. paper search), but the clarity of the tool's purpose implies its appropriate context.

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

All Semanticscholar toolsInspect
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TDQS

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, especially the core ones like get_paper, search_papers, and entity_profile. However, some pairs like ask_pipeworx and ask_pipeworx_grounded, or the polymarket tools, could cause momentary confusion, though descriptions help differentiate.

Naming Consistency2/5

Naming patterns are inconsistent: tools use verb_noun (e.g., get_paper), noun_phrase (e.g., polymarket_arbitrage), and bare verbs (e.g., forget, recall). There is no unifying pattern, and styles like 'pipeworx_feedback' vs 'search_papers' further add to the inconsistency.

Tool Count3/5

With 34 tools, the set covers a broad range of domains (academic papers, company data, prediction markets, memory, subscriptions). While the scope justifies the number, it feels slightly heavy and could benefit from consolidation or clearer grouping.

Completeness4/5

The tool set covers major functionalities for research, data retrieval, and monitoring, with only minor gaps (e.g., limited to US public companies, npm-only dependency scanning). Overall, the surface is comprehensive for the stated capabilities.

Resources