list_watersList registered waters for the account. 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 (unarchived), archived, or all. Defaults to current. |
| Name | Required | Description | Default |
|---|---|---|---|
| waters | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds value by explaining that IDs are account-local, sequential from 1, safe to show, and expected by other tools—useful behavioral context 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?
Two sentences, both purposeful. The core action is front-loaded, and the ID caveat is relevant without being verbose. No wasted words or redundant restatement of the schema.
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 operation with one documented optional parameter and an output schema, the description is complete. It covers scope, ID semantics, and cross-tool expectations. No critical call-time information is missing.
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 single optional status parameter is fully documented with enum values and default behavior. The description adds no parameter-level information, so the baseline of 3 applies.
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 states a clear verb-resource pair: 'List registered waters for the account.' It specifies scope (account-level) and distinguishes the resource from other list tools like list_recipes. The ID note reinforces what the tool returns.
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 gives no explicit guidance on when to use this tool versus siblings like list_recipes or list_beans. It does not mention filtering use cases or when status parameters should be used. The ID note implies use with other tools, but that is not a direct usage guideline.
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.