compute_ageCompute coffee age in days off roast and resting/staling verdict.
| Name | Required | Description | Default |
|---|---|---|---|
| bean_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| bean_id | Yes | ||
| verdict | Yes | ||
| age_days | Yes | ||
| warnings | Yes | ||
| roast_date | Yes | ||
| rest_window | Yes | ||
| days_off_roast | Yes | ||
| grams_remaining | Yes | ||
| days_since_opened | Yes | ||
| effective_age_days | Yes | ||
| frozen_days_excluded | Yes |
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?
Annotations already declare the tool read-only, idempotent, and non-destructive, and the description's 'Compute' wording is consistent with those. The description adds the output semantics (days off roast and verdict), but does not disclose behavior around unknown bean IDs or data availability; with annotations carrying the safety profile, this is adequate but not rich.
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 focused sentence that front-loads the action and states the key output. There is no redundant or filler 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?
For a simple tool with one self-explanatory parameter, read-only/idempotent annotations, and an output schema, the description is sufficiently complete. It states what is computed without needing to detail return fields or side effects.
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 needed to compensate by explaining bean_id, but it does not mention the parameter at all. The meaning is only inferable from the parameter name and the tool's purpose, which provides minimal but not adequate semantic guidance.
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 uses a specific verb ('Compute') and resource ('coffee age') and clarifies the output as days off roast plus a resting/staling verdict. This makes the tool's function unambiguous and distinguishes it from the sibling tools, none of which compute age.
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 intended use is implied: call this tool when you need the age of a coffee bean in days off roast and a resting/staling verdict. However, the description does not explicitly state when not to use it or mention any alternative sibling, so guidance is only implicit.
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.