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Corollary — scientific AI models, tools and databases

Explain one model, tool, database, pipeline or dataset

get_scientific_ai_details
Read-only

Full reference for one entry: what it is, how it works, key facts, uses, strengths, limitations, citation, licence, and how to run it on Corollary. Pass a name ('RFdiffusion'), an id ('esmfold2', 'nf-core/rnaseq', 'facebook/esm2_t33_650M_UR50D') or a corollary-labs.com URL.

Input Schema

NameRequiredDescriptionDefault
refYesName, id or Corollary page URL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine context by specifying the breadth of the returned reference (strengths, limitations, licence, and how to run it on Corollary), which goes beyond the annotations.

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?

Two sentences, front-loaded with the return scope and then the accepted input forms; little waste. Slightly dense enumeration of contents in one clause, but every item is meaningful to an agent.

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?

For a single-required-parameter read tool with no output schema, the description must convey the return payload, and it does so by listing the reference sections. Nothing needed to call it correctly is missing, though the absence of output schema keeps it just short of exhaustive.

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?

Schema coverage is 100% and the schema already says 'Name, id or Corollary page URL', so baseline is 3. The description earns an extra point by giving concrete accepted formats ('RFdiffusion', 'esmfold2', 'nf-core/rnaseq', 'facebook/esm2_t33_650M_UR50D'), disambiguating name vs id vs URL beyond the schema text.

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?

States a concrete resource ('Full reference for one entry') and enumerates what the entry covers (what it is, how it works, key facts, uses, strengths, limitations, citation, licence). The single-entry scope implicitly contrasts with the search/list/compare siblings, though no sibling is named explicitly.

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?

Usage is only implied: telling the agent it must supply a name, id or URL signals this is a lookup used after obtaining an identifier, but the description never says when to choose it over search_scientific_ai or compare_scientific_ai_for_task, nor any prerequisite or exclusion.

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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