Results for “fitness”

Benchmarks LLM bias by scoring responses to automatically generated open-ended questions across sensitive attributes, producing a composite fitness score from 0 to 5.

Builds a personalized fitness system by assessing your body, goals, and constraints, then designs training, nutrition, and recovery plans that adapt to real-life disruptions.

Log workouts, plan routines, track progress, and get intelligent coaching for any fitness level.

Performs a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions.

Personal trainer operations: client check-ins, workout-program delivery, progress reminders, session reminders, lead follow-up, and workout tracking. Use when an owner is a coach/personal trainer or when managing fitness clients and training routines.

Agent validation overhaul: reward weight overrides, fitness decline gate, pinned data, staged experiments

当需要启动一天，建立积极基调并获取初始能量时

Coaches runners with training plans, pace calculations, race strategies, and form analysis

分析健康目标数据、识别目标模式、评估目标进度,并提供个性化目标管理建议。支持与营养、运动、睡眠等健康数据的关联分析。

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.

Fine-tune and align language models using reinforcement learning with TRL, including SFT, DPO, PPO, GRPO, and reward model training.

Facilitate a structured sprint retrospective to surface insights and produce actionable improvements with owners and deadlines.

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting, then commit with git.

当个人希望提升自身在职业或社会中的不可替代性，以应对环境变化和不确定性时

Fix PPO training early-stop issues. Trigger when: (1) impossible drawdown values (>100%), (2) training stops too early, (3) need adaptive recovery instead of hard stop.

Agent validation v4.3.0 — Make agents act effectively by disabling harmful actions, lowering gates, and injecting cross-run learning

贺炜（体育解说）认知与表达框架（压缩蒸馏）：文学比喻嵌入赛况、克制激情、终场金句… 触发：足球诗人解说 等。非煽动球迷对立

当需要在多个领域积累独特竞争优势，避免单一技能风险时

Generates personalized workout plans with progressive overload, periodization, and exercise variations

Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.

This skill suggests using approved weight‑loss medication over no pharmacological therapy to ameliorate comorbidities and improve physical activity in adults with BMI ≥30 kg/m² or BMI ≥27 kg/m² with at least one comorbid condition. It is triggered when a clinician asks, for example, 'Should I add medication to help maintain weight loss in this patient with BMI 31 and diabetes?' or 'Is pharmacotherapy appropriate for long‑term weight control in a patient with BMI 28 and hypertension?'.

Fine-tune Gemma models locally using QLoRA, Unsloth, or TRL for SFT, DPO, and reward modeling, with dataset preparation and conversion to GGUF or LiteRT-LM.

Most teams run one test — expected peak for ten minutes — and believe they have

Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning) with support for SFT, DPO, GRPO, KTO, RLOO, and reward model training via CLI commands.

Burn HUD

Meta-skill codifying the no-wakeup-polling pattern. Describes the ScheduleWakeup anti-pattern, the fix (--auto merge + detached watcher), and when to still use wakeups. Reduces handoff spam by 80%.

Use the status-briefing skill to run `pk-reconcile session-start`, then

Build a balanced, preference-aware meal plan for a stated wellness goal using general nutrition principles.

Delivers measurement-driven performance optimization for latency, throughput, memory, and tail behavior, with correctness preservation and regression guards.