Suggests a working weight for given reps and reps-in-reserve using your recent best set or saved load anchor, then reports the basis.
Suggest a working weight for reps reps leaving rir reps in reserve, from the movement's most
recent best set (Epley estimate), falling back to the user's saved load anchor. Reports its basis.
| Name | Required | Description | Default |
|---|---|---|---|
| rir | No | ||
| reps | Yes | ||
| groupId | No | ||
| exercise | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does useful work: it discloses the estimation method (Epley), the data source (most recent best set), an explicit fallback (saved load anchor), and that the result reports its basis. It omits whether the tool mutates state or requires permissions, but 'suggest' plus the fallback chain give solid behavioral context.
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 tight sentences, front-loaded with the core function and followed by the estimation source and fallback. No filler and the key computation detail arrives before the supporting logic.
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 computation tool with no output schema and no annotations, the description explains what drives the result and that it reports its basis, which is enough to call it correctly. It falls short only on the un-described scoping parameters (`exercise`, `groupId`) and any output format hint.
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 0%, so the description must compensate. It explains `rir` as 'reps in reserve' and ties `reps` to the output, adding real meaning for two of four parameters. However `groupId` and `exercise` (the scoping parameters) are entirely undocumented in both schema and description, leaving a significant gap.
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?
States a specific verb (suggest) and resource (working weight) and even names the inputs (`reps`, `rir`) that determine the result. It is clearly distinguishable from read-oriented siblings like get_strength_profile or get_exercise_history because it computes a value rather than retrieving stored data.
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 scenario is implied (choosing a working weight for a set), but the description never states when to use this versus alternatives such as get_strength_profile or get_exercise_history, nor any prerequisites (e.g., requires prior logged sets). Usage is inferable but unstated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.