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fitpulse

Get evidence-based workout plans, exercise guides, nutrition targets, supplement analysis, injury recovery protocols, sleep optimization, and race training plans via a single API.

Instructions

FitPulse: Global fitness intelligence API. Evidence-based workout programming, nutrition science, supplement efficacy analysis, injury recovery protocols, race training plans, sleep optimization, plateau-breaki

Coverage: Global

Endpoints: • workout ($0.10): Custom workout plan • exercise ($0.10): Exercise form guide • nutrition ($0.10): Macro and nutrition targets • supplement ($0.10): Evidence-based supplement analysis • recover ($0.10): Injury recovery protocol • supplements ($0.10): Evidence-graded supplement efficacy tier list by goal • rehab ($0.10): Sports medicine rehabilitation protocol • sleep ($0.10): Athletic sleep optimization and CBT-I protocol • plateau ($0.10): Training plateau analysis and breakthrough protocol • race ($0.10): Race training plan built backwards from event date

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesWhich endpoint to call. Options: workout | exercise | nutrition | supplement | recover | supplements | rehab | sleep | plateau | race
langNolang
goalNoe.g. muscle-gain, fat-loss, strength, endurance, general-fitness
equipmentNoe.g. full gym, dumbbells-only, bodyweight (default: full gym)
levelNolevel
daysNoDays per week (default: 4)
exerciseNoe.g. barbell-squat, push-up, romanian-deadlift, pull-up
weightNoBody weight in lbs
activityNoactivity
injuryNoe.g. sprained-ankle, pulled-hamstring, rotator-cuff, shin-splints, runners-knee
budgetNoMonthly budget for supplements (e.g. $50, $100, $200)
restrictionsNoDietary restrictions or intolerances (vegan, lactose-free, etc.)
sportNoTarget sport or activity for return-to-sport phase
fitness_levelNoPre-injury fitness level (recreational, competitive, elite)
issueNoSleep issue (e.g. trouble falling asleep, early waking, poor recovery despite sleep, jet-lag)
training_scheduleNoTraining schedule context (e.g. morning workouts, evening training, two-a-days)
durationNoHow long the plateau has lasted (e.g. 6 weeks, 3 months)
current_routineNoBrief description of current training and diet approach
race_typeNoRace type (5K, 10K, half-marathon, marathon, triathlon-sprint, triathlon-olympic, ironman, OCR)
race_dateNoRace date (YYYY-MM-DD) — plan is built backwards from this date
current_fitnessNoCurrent fitness level and recent training context
runs_per_weekNoAvailable training days per week
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It mentions per-endpoint costs ($0.10) and 'Coverage: Global', but does not state whether the tool is read-only, destructive, or requires authentication. Important behaviors like rate limits, side effects, or data persistence are absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is presented as a raw line plus a list, with an apparent truncation ('plateau-breaki'). Information like 'Coverage: Global' and cost per endpoint is included but not well integrated. The structure is not front-loaded or organized for quick scanning by an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 22 parameters and no output schema, yet the description omits any details about return values, response format, or example outputs. It does not explain how parameters relate to different endpoints (e.g., 'injury' for rehab vs. 'exercise' for form). An AI agent would lack enough context to reliably craft calls and parse results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameters are already documented. The description adds minor value by listing endpoints (duplicating the action enum) and mentioning cost per endpoint. It does not clarify parameter interactions, defaults, or provide examples beyond schema descriptions. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Global fitness intelligence API' and lists specific endpoints (workout, nutrition, etc.), clearly defining the tool's scope as a multi-purpose fitness resource. It is distinct from sibling tools like 'alphapulse' or 'arbipulse' which target other domains. However, the purpose is described as a collection of endpoints rather than a single cohesive verb-resource pairing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description enumerates endpoints but provides no explicit guidance on when to use this tool versus siblings (e.g., 'alphapulse'). There is no mention of when not to use fitpulse, prerequisites, or alternatives. The list of endpoints implies use cases (e.g., 'workout' for plan generation), but no comparative or contextual advice is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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