Get community engagement metrics: memorization progress, verse mastery, difficult verses, and activity stats.
Args: collection_id: The collection ID (from browse_collections results).
| Name | Required | Description | Default |
|---|---|---|---|
| collection_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds a list of metric types, which is helpful for understanding the scope of return data, but it does not disclose behavioral nuances like permissions, rate limits, or side effects. It is not contradictory to annotations, but offers limited additive 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 extremely concise: one summary sentence listing the metrics and one parameter explanation. It is front-loaded with the core purpose and contains no unnecessary words or 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?
For a tool with a single parameter, strong annotations (read-only, idempotent), and an output schema, the description covers the essential context. It clearly explains what the tool does, what metrics are included, and how to obtain the parameter value, making it fully sufficient for an agent to invoke 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 input schema only specifies collection_id as an integer with no description. The description compensates fully by stating 'The collection ID (from browse_collections results)', which tells the agent exactly where to obtain a valid value. With 0% schema coverage, this parameter explanation is essential and highly valuable.
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 a specific verb ('get') and resource ('community engagement metrics'), and enumerates concrete metric categories (memorization progress, verse mastery, difficult verses, activity stats). This unambiguously distinguishes it from sibling tools like browse_collections and get_collection_detail.
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 gives a direct guideline for obtaining the collection_id ('from browse_collections results'), which establishes a prerequisite and a usage sequence. However, it does not explicitly contrast with get_collection_detail or state when not to use this tool, so it misses the opportunity for full usage clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a distinct purpose: browsing/searches, retrieving full details, and viewing engagement metrics. No overlap in functionality.
All tool names follow a consistent verb_noun pattern: browse_collections, get_collection_detail, get_collection_metrics. The pattern is uniform and predictable.
With 3 tools, the server is well-scoped for a read-only collection browsing and metrics use case. Each tool earns its place, and the count is within the typical 3-15 range.
The read-side coverage (browse, detail, metrics) is solid, but there are no create, update, or delete operations, and the get_collection_detail description mentions create_collection/add_verse tools that are not present. This suggests notable gaps in the expected lifecycle coverage.