get_statsGet compact flat usage stats for a grinder, machine, or bean.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The entity ID | |
| scope | Yes | The stats scope |
| Name | Required | Description | Default |
|---|---|---|---|
| brews | Yes | ||
| last_bean | No | ||
| last_used | No | ||
| grams_ground | No | ||
| effective_age | No | ||
| beans_consumed | No | ||
| grams_consumed | No | ||
| grams_remaining | No | ||
| last_grind_setting | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that stats are 'compact flat', which hints at the output shape, but it does not disclose aggregation details, time range, or any other behavioral nuances 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?
The description is a single, compact sentence that front-loads the essential information. Every word contributes: the action, the output type, and the supported scopes.
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 two-parameter read-only tool with an output schema and comprehensive annotations, the description is complete enough. The schema covers parameters, annotations cover behavior, and the output schema covers return structure, leaving no critical gaps.
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 schema already documents both parameters fully. The description adds minimal parameter meaning beyond echoing the scope enum ('grinder', 'machine', 'bean') and the notion of usage stats, so a baseline score of 3 is appropriate.
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 identifies the action ('Get'), the resource type ('usage stats'), and the supported scopes ('grinder, machine, or bean'). This distinguishes it from sibling getters like get_dial_state and get_rule, which target different kinds of information.
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 the tool: when you need usage statistics for one of the three entity types. However, it does not explicitly contrast with alternatives or state when not to use it, such as when listing entities or retrieving state information.
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 sort cleanly into register_*, list_*, set_*, and log_* families with clear resource targets. The main ambiguity is between diagnose_shot and diagnose_preview, which are deliberately similar, and between get_dial_state and suggest_next_step, but the descriptions resolve these reasonably well.
Naming is overwhelmingly consistent snake_case verb_noun, such as register_coffee, list_shots, update_shot, and set_active. Minor exceptions like kb_changelog next to get_kb_version and grinder_math break the pattern slightly.
With 34 tools, the surface is well over the 25+ too-many threshold. The resource families are individually clear, but the assistant would be easier to navigate with fewer, more consolidated tools or less KB introspection surface.
The core dialing workflow is well covered: registration, shot logging, diagnosis, dial state, recipes, and maintenance. However, most registered entities such as grinders, machines, waters, scales, and programs have create+list but no update/delete, and recipes have no unlock/delete lifecycle.