Remember Me Collections

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

Adds context about the raw cover image field and its behavior beyond what annotations (readOnly) already convey, but lacks details on rate limits or authentication.

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?

Starts with a clear one-sentence summary, followed by a brief note on the image field, then a structured Args list. No redundant content.

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?

Covers key usage aspects (search, filter, sort, pagination) and a unique image behavior note; output schema presumably handles field details, so overall sufficiently 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?

Args section clearly explains each parameter's purpose and defaults (e.g., ordering options, pagination), compensating for 0% schema description coverage.

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 browses published Bible verse collections with search, filter, and sort capabilities, distinguishing it from siblings like get_collection_detail which target specific collections.

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?

Implies usage for browsing lists, and sibling names suggest alternatives, but 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.

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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context about the image field: it is the raw URL from the publisher, may be null, and behaves consistently with create_collection/add_verse. This goes beyond what annotations provide.

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 paragraphs: the first sentence front-loads the main purpose. The second paragraph efficiently covers the important image behavior nuance. Every sentence adds value, and the description is well-structured without unnecessary text.

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 output schema exists, the description need not detail return values. It covers purpose, usage context, and a key behavioral detail about raw vs. computed images. For a single-parameter read-only tool, this is complete and informative.

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 sole parameter collection_id is described as 'The collection ID (from browse_collections results).' The input schema only specifies type and required but gives no source or context. With 0% schema description coverage, this addition fully compensates, clarifying where to obtain the value.

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 'Get full details of a published collection including all verse text, references, and topics.' It uses a specific verb ('Get') and resource ('collection detail'), and the name itself distinguishes from siblings like 'browse_collections' and 'get_collection_metrics', which cover listing and metrics respectively.

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 advises that the collection_id comes from browse_collections results, implying usage after browsing. It does not explicitly state when not to use or compare to alternatives, but the context is sufficient for the agent to infer appropriate usage.

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?

Annotations already provide key behavioral hints (readOnlyHint: true, destructiveHint: false, etc.), so the description's burden is lower. It adds useful context by specifying the types of metrics retrieved (e.g., memorization progress, activity stats), which isn't covered by annotations. No contradictions with annotations are present, and it offers additional operational insight.

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 appropriately sized and front-loaded, starting with the core purpose in the first sentence and following with parameter details. Every sentence adds value, with no wasted words, though the structure could be slightly more polished (e.g., bullet points for metrics).

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 tool's complexity (simple read operation with one parameter), rich annotations (covering safety and idempotency), and the presence of an output schema (which handles return values), the description is sufficiently complete. It explains what metrics are retrieved and parameter semantics, addressing key gaps without overloading with redundant information.

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 0%, so the description must compensate. It explains that 'collection_id' is 'The collection ID (from browse_collections results)', adding semantic meaning about the parameter's source and purpose beyond the schema's basic type and title. This effectively clarifies the parameter, though it could be more detailed (e.g., format or constraints).

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 purpose with specific verbs ('Get community engagement metrics') and resources ('memorization progress, verse mastery, difficult verses, and activity stats'), making it easy to understand what data is retrieved. However, it doesn't explicitly differentiate from sibling tools like 'get_collection_detail', which might also provide collection-related information, so it falls short of a perfect score.

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 by referencing 'collection_id (from browse_collections results)', suggesting a workflow where this tool follows browsing, but it doesn't explicitly state when to use this tool versus alternatives like 'get_collection_detail' or provide clear exclusions. This gives some context but lacks detailed guidance on tool selection.

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