提示词
提示词工程与模板
agent-tracing
lobehub
'Agent tracing CLI for execution snapshots. Use for agent-tracing, traces, snapshots, LLM call inspection, context engine data, agent step analysis, execution debugging, or pulling remote/production traces ("拉线上 tracing") by operation id. Also the first stop for debugging agent tool calls — wrong or missing tool_calls, unexpected tool arguments or results, which tools were available at a step, or why a tool ran where it did.'
model-bank-metadata
lobehub
'Backfill and maintain model-bank metadata (knowledgeCutoff, family, generation). Use when adding models, fixing cutoff/family data, running a metadata sweep across aiModels providers, or researching official knowledge cutoffs.'
builtin-tool
lobehub
'Build LobeHub builtin tool packages. Use when adding agent-callable tools, manifests, executors, runtimes, inspectors, renders, placeholders, streaming, interventions, portals, or tool registries.'
ai-md
sickn33
"Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance."
ai-agent-development
sickn33
"AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents."
ai-wrapper-product
sickn33
Expert in building products that wrap AI APIs (OpenAI, Anthropic,
create-prompt
microsoft
'Create a reusable prompt file (.prompt.md) for a common task.'
otel
microsoft
OpenTelemetry instrumentation for the Copilot Chat extension — covers the four agent execution paths, the IOTelService abstraction, span/metric/event conventions, and the relationship between code and the user/developer monitoring docs. Use when adding/changing OTel spans, metrics, or events; instrumenting a new agent surface; touching the Copilot CLI bridge or Claude span emission; or updating extensions/copilot/docs/monitoring/agent_monitoring*.md.
opportunity-solution-tree
phuryn
"Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when structuring discovery work, mapping opportunities to solutions, or deciding what to build next."
identify-assumptions-new
phuryn
"Identify risky assumptions for a new product idea across 8 risk categories including Go-to-Market, Strategy, and Team. Use when evaluating startup risks, assessing a new product concept, or mapping assumptions for a new venture."
smoke-test
mastra-ai
Create a Mastra project using create-mastra and smoke test the studio in Chrome using Chrome MCP server
e2e-tests-studio
mastra-ai
REQUIRED when modifying any file in packages/playground-ui or packages/playground. Triggers on: React component creation/modification/refactoring, UI changes, new playground features, bug fixes affecting studio UI. Generates Playwright E2E tests that validate PRODUCT BEHAVIOR, not just UI states.
experiments
langwatch
Create and run LangWatch experiments for pre-deployment batch testing. Use when the user wants to test an agent against a dataset, compare prompts or models, benchmark quality, detect regressions, or add a CI quality gate. Do not use for production monitoring or guardrails.
tracing
langwatch
Add LangWatch tracing and observability to your code. Use for both onboarding (instrument an entire codebase) and targeted operations (add tracing to a specific function or module). Supports Python and TypeScript with all major frameworks.
scenarios
langwatch
Test your AI agent with simulation-based scenarios. Covers writing scenario test code (Scenario SDK), creating platform scenarios via the langwatch CLI against a connected agent, reading the run parameters that agent declares so the scenarios and comparison runs turn its real levers, and red teaming for security vulnerabilities. Auto-detects whether to use code or platform approach based on context.
prompts
langwatch
Version and manage your agent's prompts with LangWatch Prompts CLI. Use for both onboarding (set up prompt versioning for an entire codebase) and targeted operations (version a specific prompt, create a new prompt version). Supports Python and TypeScript.
evaluate-multimodal
langwatch
Evaluate multimodal AI agents that process images, audio, PDFs, or other files. Sets up evaluations using LangWatch's LLM-as-judge with image inputs, Scenario's multimodal testing, and document parsing evaluation patterns. Use when your agent handles non-text inputs.
tmux
elizaOS
Remote-control tmux sessions for interactive CLIs by sending keystrokes, capturing pane output, and managing terminal multiplexer windows. Enables parallel coding-agent orchestration, background process management, and REPL interaction via sockets. Use when the agent needs to launch, monitor, or coordinate long-running terminal processes, run multiple agents in parallel, interact with a Python REPL, or scrape live shell output from a persistent session.
ask
git-ai-project
"Use this when you are exploring the codebase. It lets you ask the AI who wrote code questions about how things work and why they chose to build things the way they did. Think of it as asking the engineer who wrote the code for help understanding it."
prompt-guard
Orchestra-Research
Meta's 86M prompt injection and jailbreak detector. Filters malicious prompts and third-party data for LLM apps. 99%+ TPR, <1% FPR. Fast (<2ms GPU). Multilingual (8 languages). Deploy with HuggingFace or batch processing for RAG security.
llama-factory
Orchestra-Research
Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support
openai-whisper-api
openclaw
"OpenAI Audio Transcriptions API via curl; gpt-4o-transcribe, mini, diarize, or whisper-1."
oracle
openclaw
"Oracle CLI second-model review/debug/refactor/design with selected files, dry-run token checks, API or browser engine."
gemini
openclaw
"Gemini CLI one-shot prompts, summaries, generation, skills, hooks, MCP, or Gemma routing."