list_beansList coffee beans registered for the account, with status filter. The id on each row is the number this account knows that record by, counting from 1 — safe to show, and what other tools expect back.
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | Filter by status: current, archived, or all. Defaults to current. |
| Name | Required | Description | Default |
|---|---|---|---|
| beans | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds valuable non-obvious behavioral context: row ids are account-local, start at 1, are safe to show, and are what other tools expect. This is genuine information beyond what structured annotations and schema 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 two sentences with no filler. The primary action and scope are front-loaded, and the second sentence provides important ID guidance without excess verbosity.
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 read-only list with one optional parameter, a comprehensive enum in the schema, rich annotations, and an output schema, the description is complete. It covers the tool's scope, filtering behavior, and the key ID convention needed for downstream use.
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 coverage is 100%: the status parameter has both an enum and a descriptive default. The description merely refers to 'status filter' without adding parameter-level detail, so baseline 3 is appropriate since the schema carries the full semantic load.
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 opens with a specific verb and resource: 'List coffee beans registered for the account.' It also names the status filter, and the account scoping distinguishes it from sibling list_* tools such as list_shots and list_machines. The matching title 'List bags of coffee' is consistent with the described functionality.
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 makes clear what is being listed and that an optional status filter is available, which gives the agent adequate context for selecting this tool over resource-specific siblings. It does not explicitly state when not to use it, but the distinct resource and schema-provided defaults make the intended usage clear.
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 maps to a distinct resource or action: register_* and list_* are separated by entity, shot tools are split into log/update/delete/diagnose, and the two diagnose variants are explicitly differentiated by dry-run vs. logged evaluation. There is no meaningful overlap that would make an agent choose the wrong tool if it reads the descriptions.
The vast majority of tools follow a consistent verb_noun snake_case pattern: register_*, list_*, set_*, update_*, log_*, get_*. The only deviations are noun-first compound names like grinder_math and kb_changelog, which are still readable and do not break the overall predictability.
At 34 tools, this server exceeds the 25+ threshold where the interface becomes heavy for an agent to navigate. Many of the tools are simple register_/List_ pairs across seven entity types, which inflates the surface area even though each individual tool is understandable.
Core workflows are well covered: logging, updating, deleting, and diagnosing shots; maintaining equipment; and navigating machine state. However, there are notable lifecycle gaps such as no way to list or delete registered programs, no update/delete operations for most equipment types, and no recipe deletion or unlock, which can leave an agent stuck after certain user requests.