Results for “recommender”
16 skillspk-model-setup
Use the model-recommender skill, Workflow D (Setup Questionnaire), to configure model access and project-level preferences.
0
pk-model-refresh
Use the model-recommender skill, Workflow C (Roster Refresh), to research and update the model roster from live benchmarks.
0
More results
pk-route
Use the model-recommender skill, Workflow B (Task Router), to route the following task to the optimal model + version + effort: $ARGUMENTS.
0
navigate
Recommends the best skill, agent, or command for a given task by classifying intent and scanning available tools.
0
model-recommender
Recommend the right AI model for a task by scoring candidates across six dimensions (Reasoning, Engineering, Speed, Breadth, Reliability, Governance) and displaying a spider-chart profile.
0 · bundle
prompt-optimizer
Creates, optimizes, and iteratively refines agent prompts, system prompts, developer prompts, and reusable prompt templates with evals.
845 · bundle
nemo-mbridge-recipe-recommender
Indexes Megatron Bridge recipes and recommends the best starting config based on model, GPU count, and training goal.
2.2k · bundle
nemotron-retrieval-recipes
Plan, debug, tune, evaluate, export, or deploy public Nemotron embedding and reranking retrieval recipes using the current checkout.
2.2k · bundle
bmad-advanced-elicitation
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
12 · bundle
bmad-advanced-elicitation
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
1 · bundle
bmad-advanced-elicitation
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
1 · bundle
cx-regulated-advice-boundary
Use to find where support agents cross from information into regulated advice or a personal recommendation, and to design the boundary so they can still be helpful. Trigger for "are agents giving advice", "where's the line between information and advice", "should agents recommend a product", guidance versus advice boundary, agents answering "what would you do", or a complaint that an agent recommended something.
1
project-review
针对 Modular RAG MCP Server 项目的老师式复习 Agent。按章节带领用户系统复习项目知识点,每道题互动问答、给出参考答案,复习结束后记录掌握进度,每次开始时回顾上次进度并建议继续或复习。Use when user says '复习项目', '帮我复习', '带我复习', '开始复习', '项目复习', 'review project', 'study review', '学习复习', '复盘', or wants to systematically review and study the project.
1 · bundle
prompt-optimizer
Prompt Optimizer
0
prompt-optimizer
Analyzes draft prompts, identifies intent and gaps, matches ECC components, and outputs an optimized prompt for the user to paste and run. Advisory only, never executes the task.
0
stop-senior-care-referral-cascade
Map and organize unwanted calls, texts, or emails after a U.S. senior-care referral inquiry by using GeezerKeeper's live public MCP for current network exit routes, separate provider jobs, unfilled request templates, duplicate-referral deadline facts, and current free or paid workflow fit. Use when a person asks why a senior-care marketplace or several providers are contacting them, how to opt out, how to prepare a stop-contact request, how to compare inquiry consequences before submitting a form, or how a senior-living professional should track direct-versus-network referrals. Do not use for emergencies, care placement, legal or medical advice, automatic sending, unknown-caller identity claims, or transmitting personal information.