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get_next_read

Find the next recommended reading for any Jewish text reference. Provide a text reference to receive a related suggestion from the Sefaria library.

Instructions

Get the next recommended reading based on a reference.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trefYesThe text reference.

Schema Changelog

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

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, yet it only restates the operation without addressing side effects, ordering, determinism, or error conditions. The 'get' verb implies read-only but adds no behavioral detail beyond what the name and schema already suggest.

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 a single sentence with no filler and gets straight to the point. It is appropriately concise for the tool's simplicity, though it sacrifices completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description is too thin to be fully self-sufficient. It doesn't explain what a 'recommended reading' looks like, what tref should be, or how this differs from closely related tools, so an agent would likely need to inspect other definitions to invoke it correctly.

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%, so the baseline is 3. The description adds the semantic link that tref is the 'reference' used to compute the 'next recommended reading,' which is mildly informative but does not elaborate on format, required characteristics, or relationship to other tools' parameters.

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 states a specific verb ('get') and resource ('next recommended reading') and specifies that it is based on a reference, which is clear enough to distinguish it from generic get_text or get_random_text. However, it does not explicitly name or contrast any sibling tool, so it earns a 4 rather than 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to choose this tool over siblings such as get_related, get_recommended_topics, or get_random_text. No context, exclusions, or alternative references are given, leaving the selection entirely to the agent's inference.

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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