readiness_checkinRecord how the athlete feels today (energy, sleep, soreness — each 1–5). The engine scores readiness and, on the next get_todays_session, reshapes the workout accordingly (reduce volume / reduce intensity / recovery day). Returns the readiness score + modifier.
| Name | Required | Description | Default |
|---|---|---|---|
| sleep | Yes | 1 terrible … 5 great | |
| energy | Yes | 1 drained … 5 great | |
| soreness | Yes | 1 none … 5 very sore |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the three inputs, the readiness scoring, the workout reshaping (reduce volume/intensity/recovery day), and the return value (score + modifier). It does not mention idempotency or repeated submissions, but the principal side effects are transparent.
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: the first states the purpose and inputs, the second covers scoring, downstream effects, and return value. Every word earns its place.
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?
The tool is simple with 3 required integer parameters. The description covers input, behavior, side effects, and return value. Given the full schema and the clear linkage to get_todays_session, this is 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?
The schema already describes each parameter's meaning and range (1-5), so the description's 'each 1-5' adds nothing new. The mention of readiness scoring provides some context, but the parameter semantics are otherwise fully covered by the schema.
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 the verb 'Record' and resource 'readiness check-in' while specifying the three data points (energy, sleep, soreness). It clearly differentiates from siblings like log_workout and get_todays_session by stating its unique effect on the next session.
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 context is explicit: use it to record how the athlete feels today, and the description explains how it impacts the next get_todays_session. It stops short of naming alternatives or stating when not to use it, but the intended usage is 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 targets a distinct action or resource: program retrieval, session guidance, workout logging, readiness check-in, exercise swaps, nutrition targets, and meal planning. Even the closely related list_swap_options and swap_exercise have clear separation (viewing alternatives vs. applying a change). No two tools could be reasonably confused.
Tool names are predominantly snake_case with a verb_noun pattern (get_program, list_swap_options, log_workout, regenerate_program, swap_exercise). However, a few are plain nouns (changelog, meal_plan, nutrition_targets) and readiness_checkin is a noun phrase, breaking the strict verb-first convention. This is a minor deviation that does not hinder readability.
With 10 tools, the server is well-scoped for a fitness coaching domain. Every tool addresses an essential aspect of the coaching loop: program viewing, daily session delivery, workout logging, readiness tracking, nutrition guidance, exercise modification, and explanation of changes. The count is within the ideal range and none feel redundant.
The tool surface covers the core lifecycle: get program, regenerate program, view today's session, log workout, check in readiness, swap exercises, and access nutrition targets and meal plans. Notable gaps include no explicit workout history/retrospective tool and no direct profile management, but these are likely handled externally or can be worked around. The inclusion of a changelog nicely closes the feedback loop.