Same shape as librelink_get_glucose_stats but filtered to "today" in a chosen IANA timezone, plus hypo_events_70 / hyper_events_180 counts. 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 | ||
| timezone | No | UTC | |
| 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 destructiveHint=false. The description adds that data is read-only CGM and not for medical decisions, plus mentions bulk execution support, which goes beyond annotations.
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 concise (two sentences) with key information front-loaded. However, it could benefit from more detail on parameters without becoming verbose.
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?
No output schema, but description relies on referencing sibling librelink_get_glucose_stats for return shape, which is incomplete. Parameters are under-described, and there is no guidance on how to use the bulk feature or what the output looks like.
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 only mentions 'timezone' implicitly and 'patient_ids' for bulk. Parameters like account, patient_id, target_low, target_high are not explained, leaving significant ambiguity.
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 explicitly states it's 'Same shape as librelink_get_glucose_stats but filtered to today in a chosen IANA timezone, plus hypo_events_70 / hyper_events_180 counts.' This clearly identifies the tool's purpose and differentiates it from its sibling librelink_get_glucose_stats.
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 when to use (for today's summary vs. general stats) and provides a medical disclaimer. However, it lacks explicit statements on when not to use or detailed alternative comparisons besides referencing the sibling.
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.