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BGPT Scientific Data

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Search scientific evidence

search_papers
Read-onlyIdempotent

Search claim-level evidence extracted from full-text scientific papers.

Args: query: Search terms (e.g. "CRISPR gene editing efficiency"). SHORT, concise queries are best. English language only. Use days_back, num_results, min_citations, and study_type instead of adding years or filters to the query. num_results: Number of results to return (1-100, default 16). First 50 results are free, then metered per result for paid users. days_back: Only return papers published within the last N days. min_citations: Only return papers with at least this many references cited. study_type: Only return papers of this study type. One of: primary study | systematic review | meta-analysis | narrative review | protocol | dataset | commentary | other. output_format: "evidence" for compact claim-level evidence (default), "legacy" for original paper metadata, or "full" for both.

Returns: An envelope whose results list contains papers with claims, experiments, exact results, demonstrated scope, limitations, and provenance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
days_backNo
study_typeNo
num_resultsNo
min_citationsNo
output_formatNoevidence

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / min_citations
      Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}
    • addedInput schema / properties / study_type
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}
  2. Changed5 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedInput schema / properties / days_back / description
      Removed value: -"Only return papers published within the last N days."
    • removedInput schema / properties / num_results / description
      Removed value: -"Number of results to return (1-100, default 16). First 50 results are free, then billed at $0.01/result for paid users."
    • addedInput schema / properties / output_format
      Added value: +{
+  "default": "evidence",
+  "type": "string"
+}
    • removedInput schema / properties / query / description
      Removed value: -"Search terms (e.g. \"CRISPR gene editing efficiency\") Short, concise queries are best. English language only. Don't include years or filters — use the days_back and num_results params instead."
  3. Changed4 schema fields changed
    • removedInput schema / properties / api_key
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null
-}
    • addedInput schema / properties / days_back / description
      Added value: +"Only return papers published within the last N days."
    • addedInput schema / properties / num_results / description
      Added value: +"Number of results to return (1-100, default 16). First 50 results are free, then billed at $0.01/result for paid users."
    • addedInput schema / properties / query / description
      Added value: +"Search terms (e.g. \"CRISPR gene editing efficiency\") Short, concise queries are best. English language only. Don't include years or filters — use the days_back and num_results params instead."
  4. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already mark the operation readOnly and idempotent, and the description adds non-obvious behavior: claim-level extraction, English-only queries, a metering/rate-limit note after 50 results, and the envelope shape with claims/experiments/provenance. No contradiction with 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 main purpose sentence is front-loaded, followed by a lean Arg/Returns structure. Every line adds usable detail, and there is no repetition of schema or annotations.

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?

For a six-parameter tool with no schema descriptions and one sibling, the description is complete: all parameters are explained, the return envelope is summarized, and annotations already cover safety. An agent can select and call this tool without further docs.

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

Parameters4/5

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

With 0% schema coverage, the description does the work: it supplies defaults, ranges, allowed values for study_type and output_format, and query style guidance. The only weakness is that min_citations is defined as 'references cited', which could be confused with a paper's reference count rather than its citation count.

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?

The description names a specific verb and resource: 'Search claim-level evidence extracted from full-text scientific papers.' This clearly differentiates by scope from a single-paper lookup, but it never explicitly references lookup_paper, so it is not fully sibling-distinctive.

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?

It provides clear operating guidance: short English queries, use days_back/num_results/min_citations/study_type instead of stuffing filters into query text, and output_format choices. This tells an agent how to invoke the tool correctly, but it does not state when to prefer lookup_paper over search_papers.

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

All BGPT Scientific Data toolsInspect
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