Hebrew Bible (Tanakh)

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. It explicitly discloses pagination behavior ('Results are paginated; pass the returned cursor to get more') and implies a read-only operation via 'List...'. It also clarifies that the subject parameter accepts both codes from list_subjects and arbitrary topic tags. These details add meaningful beyond-schema context, though it doesn't describe error handling or the exact response shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, with the verb and resource in the first clause. It front-loads the action, provides examples inline, and includes a succinct note on pagination. Every sentence earns its place, with no redundant or vague filler.

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

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

The tool is a list operation with no output schema, so the description is the primary source for return value expectations. It explains that it returns study plans and articles, mentions pagination, and crosses references to list_subjects. This is sufficient for a simple browsing tool, though it does not detail the structure of the returned items (e.g., whether they are IDs or titles). Given the sibling tools and simple nature, the description is adequately complete.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds additional meaning beyond the schema, particularly for the 'subject' parameter: it explains that both subject codes from list_subjects and free-form topic tags are accepted, and gives concrete examples ('parsha', 'jonah', 'psalm 23'). It also clarifies the 'cursor' parameter's usage by saying 'pass the returned cursor to get more.' This enriches the parameter semantics beyond the schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'List study plans and articles for a subject or topic.' It names the resource type and distinguishes from siblings by focusing on browsing multiple items rather than retrieving a single chapter, plan, or verse. Examples of subject codes and topic tags make the scope immediately understandable.

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

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

The description provides clear guidance on when to use the tool: when you have a subject code (from list_subjects) or a topic tag. It does not explicitly mention alternatives like 'use get_plan for a specific plan,' but it implies this by describing a list/browse function. The reference to list_subjects is a useful cross-tool pointer. No exclusions or 'when not to use' are stated, but the context is clear enough.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clarifies the scope (full chapter, every verse) but does not mention error handling, output format details, or any operational constraints like rate limits. For a read-only retrieval tool, the lack of side-effect warnings is acceptable, but additional behavioral context 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences: the first states the core function, the second provides a critical prerequisite and reinforces the schema's language enum. There is no redundant or fluff content, front-loaded appropriately.

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

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

The description covers the tool's purpose, identifies the required prerequisite (list_books), and mentions language options. It lacks explicit output structure guidance, but the phrase 'full text of a chapter' provides a basic return description. Given the tool's relative simplicity and the presence of sibling tools, this is adequate context.

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

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

All three parameters are fully documented in the schema with descriptions and enums, providing 100% coverage. The description adds a prerequisite tip about list_books for the book parameter, but the language enum reference merely duplicates schema information. With high schema coverage, the description adds limited parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Return') and resource ('chapter from the Hebrew Bible / Tanach'), explicitly noting it returns every verse, which distinguishes it from the sibling tool get_verse. This provides clear, unambiguous purpose.

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

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

The description explicitly instructs users to call list_books first to obtain valid book names, and points to the language enum for available languages. It does not explicitly name get_verse as an alternative, but the phrase 'every verse' implies it differs from the single-verse sibling tool. This is clear context though not exhaustive.

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

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

With no annotations provided, the description carries the transparency burden. It discloses the returned fields and explicitly notes that only the first 7 days of the schedule are shown, which is a meaningful behavioral constraint. It does not mention error behavior or permissions, but for a read-only lookup this is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two focused sentences: the first states the tool's purpose and output, the second gives essential usage context for the plan id. No wasted words; information is front-loaded and efficiently organized.

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

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

The description is complete for a simple lookup tool: it lists the return fields and the id source. It does not clarify whether more than 7 days can be retrieved, but given the sibling tools and simplicity, this is a minor gap. No output schema exists, so the description's enumeration of return fields is helpful.

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

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

Schema coverage is 100% with descriptions for both parameters. The description adds value by explaining how to obtain the plan id (from a browse_subject link, final path segment) and provides a concrete example. This goes beyond the schema, making parameter semantics clearer.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Get'), a clear resource ('study plan'), and explicitly enumerates what is included: title, description, total length, and the first 7 days of the schedule. This clearly distinguishes it from sibling tools like get_chapter and get_verse.

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

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

Provides practical guidance by explaining that the plan id comes from a browse_subject link and that the final path segment is the id, with an example. This implies the appropriate usage context (after browsing subjects), though it does not explicitly name alternative tools or exclusion conditions.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It states the core behavior of returning text for a specific verse, which is straightforward and non-destructive, but does not mention error handling, language variations, or any side effects. This is adequate for a simple read-only tool but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exactly two sentences: purpose and example first, then a practical usage tip. It is front-loaded, concise, and contains no unnecessary verbiage.

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

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

For a simple lookup tool with no output schema, the description sufficiently explains the return value (the verse text) and provides an example. It could mention the language parameter or the alternative get_chapter tool, but the schema fills those gaps, making it fairly complete for the tool's complexity.

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

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

Schema coverage is 100%, with all parameters described, so the baseline is 3. The description adds a useful composite example and a tip about using list_books for book names, but these are minor supplements to already well-documented schema fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns the text of one specific verse from the Hebrew Bible/Tanach, with a concrete example (Genesis 1:1). It implicitly distinguishes from get_chapter by emphasizing 'one specific verse,' but does not explicitly compare itself to sibling tools.

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

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

The description implies usage when needing a single verse and provides a helpful tip to use list_books for valid book names. However, it does not explicitly state when to prefer this over get_chapter or other alternatives, leaving usage context partially implicit.

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

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

With no annotations provided, the description carries full burden. It clearly states what the tool does (returns list with specific fields) and its purpose (name discovery). It does not mention edge cases like sorting or pagination, but for a simple list-read operation, the behavior is fully disclosed for practical purposes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no fluff. The first sentence states the action and output; the second gives a practical use case. Every word earns its place.

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

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

Given the simple nature (1 optional param, no output schema), the description fully covers what to expect from the tool and how to use it in a workflow. It names the output fields, which is sufficient for a list operation.

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

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

Schema coverage is 100% with language parameter already described as ISO code for localized names. The description reinforces this by mentioning 'localized name' but adds no new semantics beyond linking the parameter to the output.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('List every book available') and details the output fields (English name, localized name, first chapter link). It clearly distinguishes itself from siblings like get_chapter and get_verse by framing itself as the discovery tool for book names.

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

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

Explicitly instructs 'Call this to discover valid book names for get_chapter / get_verse,' providing a clear use case and linking to related tools. This is direct when-to-use guidance that a sibling-focused alternative lacks.

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

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

No annotations are provided, so the description must disclose behavior. It explains that each result returns a code usable by browse_subject, which is valuable, but it does not explicitly state that the operation is read-only or describe the response format. This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three concise sentences: first gives purpose and examples, second explains the return behavior, third states when to call. Every sentence earns its place with no unnecessary words.

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

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

For a simple list tool with one optional parameter and no output schema, the description covers purpose, examples, the return code behavior, and the usage workflow. It could slightly elaborate on the exact output structure, but the provided information is sufficient for an agent to invoke the tool correctly.

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

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

The schema covers 100% of the single optional parameter with a detailed description and enum values. The tool description does not add extra parameter information beyond the schema, so the baseline score of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists browseable subjects (categories) with concrete examples, and distinguishes it from the sibling browse_subject by explaining it returns codes for that follow-up tool. The verb+resource is specific: list subjects.

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

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

The description explicitly says 'Call this to discover what is available before browsing' and instructs that each returned code is passed to browse_subject, providing clear workflow context. It does not explicitly exclude other sibling tools, but the guidance is sufficient for the intended use.

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