list_grindersList grinders 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 |
|---|---|---|---|
| grinders | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already establish read-only, idempotent, non-destructive behavior. The description usefully adds meaning about the returned `id` semantics: it is account-specific, stable, safe to display, and expected as input by other tools. This is valuable behavioral context beyond the 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 two sentences with no fluff. It front-loads the core purpose and status filter, then adds the important ID caveat in a compact second sentence.
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 list tool with one optional parameter, full schema coverage, an output schema, and complete annotations, the description covers everything an agent needs to call it correctly. It also clarifies the subtle ID numbering behavior, making it effectively complete.
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%, with the single `status` parameter fully documented including its enum values and default. The description only mentions 'status filter' without adding new semantic detail, so the schema already carries the full burden; the baseline 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 states the tool's function: listing grinders registered for the account, with an optional status filter. This distinguishes it from sibling list_* tools by specifying the resource ('grinders') and its account scope.
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 says what the tool does but gives no guidance on when to prefer it over alternatives such as list_machines or register_grinder. It does not state exclusions, prerequisites, or scenarios where another tool would be more appropriate, leaving that entirely to inference.
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.