autosearch_verify_doi
Verify a DOI via Crossref. Returns validity, title, authors, year, journal.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| doi | Yes | DOI string with or without https://doi.org/ prefix |
autosearch
by uk.exatoshi
TDQS
A4.1/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavior. It accurately describes the tool as a read-only verification that returns metadata, implying no side effects. However, it does not explicitly state safe, non-destructive behavior, which would be beneficial.
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 (two sentences) and front-loaded with the primary verb 'Verify', efficiently summarizing purpose and output without unnecessary words.
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 simple verification tool with one parameter and no output schema, the description is fully complete. It explains the action, the data source (Crossref), and the returned fields, leaving no ambiguity.
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?
The input schema provides 100% coverage for the single parameter 'doi', including a clear description of accepted formats. The description adds no further parameter information, so it meets the baseline for full schema coverage.
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's purpose: 'Verify a DOI via Crossref.' It specifies the output fields (validity, title, authors, year, journal), making the functionality unambiguous and distinguishable from sibling tools like autosearch_run_research or autosearch_search_evidence.
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?
The description implies usage context (DOI verification via Crossref) but does not specify when to prefer this tool over alternatives or mention any prerequisites or exclusions. No explicit 'when to use' or 'when not to use' guidance is 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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TDQS
A3.7/5.0
Disambiguation5/5
Each tool has a distinct and clearly separated purpose: launching, status checking, listing runs, retrieving papers, searching evidence, and verifying DOIs. No two tools overlap in functionality.
Naming Consistency5/5
All tools follow a consistent 'autosearch_verb_noun' pattern in snake_case, with verbs like get, list, run, search, verify. The prefix is uniform, making the set predictable.
Tool Count5/5
With 6 tools, the server is well-scoped. It covers the essential operations for AI research automation without being excessive or insufficient.
Completeness4/5
The tools cover the core workflow of launching, monitoring, retrieving results, and auxiliary searches. Missing operations like canceling or deleting runs, but the surface is largely complete for typical use.