Compute time-in-range, average, min/max, and latest-point snapshot from the current graph window (~12h) for a connection. Defaults: target 70-180 mg/dL. Read-only CGM data — not for medical decisions without clinician review.
Bulk support: accepts patient_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| patient_id | No | ||
| target_low | No | ||
| patient_ids | No | ||
| target_high | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true. Description adds useful context: data source is 'current graph window (~12h)', includes a medical disclaimer, and notes batch execution via patient_ids. No contradiction with annotations. Adds value 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 clear, front-loaded sentences with no redundancy. Every word adds value: purpose, scope, defaults, disclaimer, and bulk support are all conveyed efficiently.
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 5 parameters, no required fields, no output schema, and helpful annotations, the description covers the tool's purpose, scope, defaults, and bulk capability. Lacks detail on return format (e.g., not describing the 'latest-point snapshot' structure), but overall sufficient for an agent to understand when to invoke it.
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 documentation coverage is 0%, so description must compensate. It explains defaults for target_low and target_high (70 and 180 mg/dL) and the purpose of patient_ids (bulk execution). However, account and patient_id parameters are not described, leaving ambiguity. Partial compensation.
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?
Description uses specific verb 'Compute' and names resources 'time-in-range, average, min/max, latest-point snapshot' from a defined scope 'current graph window (~12h)'. This clearly distinguishes it from sibling tools like librelink_get_current_glucose (single reading) and librelink_get_today_summary (full day).
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 cautionary note 'not for medical decisions without clinician review' and mentions bulk support, but does not explicitly state when to prefer this tool over siblings (e.g., when a statistical summary is needed vs. raw readings). Implicit guidance exists but not explicit enough.
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.
Most tools are clearly distinct by function, but librelink_list_accounts and librelink_list_connections are exact aliases, causing confusion. Some glucose tools have overlapping outputs (e.g., librelink_get_current_glucose vs librelink_get_latest_reading), though descriptions help differentiate them.
CGM data tools consistently use the librelink_ prefix, but authentication, connect, marketplace, report_bug, show_version, and toolkit_info lack the prefix, mixing conventions. This inconsistency makes the tool set feel disjointed.
With 16 tools, the set is slightly larger than needed, but it covers the main CGM functionalities plus platform utilities. The number is still reasonable and manageable, with each tool serving a specific purpose.
The CGM data tools provide comprehensive read-only access (current, graph, stats, logbook, etc.), but there are no write operations (e.g., setting targets) or historical data beyond ~12-14 days. The inclusion of marketplace and configuration tools feels out of scope but does not leave critical gaps for the stated domain.