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name: prompt-examples description: "Find, classify, adapt, and validate PromptCraft-Robotics markdown prompt examples across robotics task families." metadata: disco-role: operating disable-model-invocation: true license: MIT

Prompt examples

Use this sub-skill when a user asks for help with the PromptCraft-Robotics markdown examples: selecting an example family, adapting a prompt to a new scene, preserving the repo's response style, or checking whether a draft prompt follows the repository patterns.

This sub-skill covers text prompt examples. For the ChatGPT-AirSim runtime sample, route to ../airsim-simulator/.

Use this sub-skill for

• choosing an example category from a user request;
• summarizing the repository's robotics example families;
• adapting an aerial, embodied, manipulation, multi-robot, visual-servoing, or basic robotics prompt;
• preserving the Question / Code / Reason response pattern;
• validating a new draft prompt before it is shared or used.

Do not use this sub-skill for

• installing or running the AirSim chatbot sample;
• diagnosing OpenAI API keys or AirSim simulator connectivity;
• generic LLM prompting that has no robotics control, scene, object, or robot-function context.

Start here

1. Read references/category-map.md to choose the relevant example family.
2. Read references/prompt-patterns.md to preserve the repo's style.
3. Read references/adaptation-guide.md before rewriting an example for a new robot, scene, object set, or sensor.
4. Run scripts/validate-prompt-example.py against a draft markdown prompt when a structural check is useful.
5. Use references/troubleshooting.md when the prompt is ambiguous, invents functions, or mixes coordinate conventions.

Common decisions

• If the user wants to run the AirSim sample, route to ../airsim-simulator/.
• If the user wants a prompt to match a robotics task, choose the category by robot, sensor, and action family.
• If the scene has duplicate objects, keep the repository's clarification behavior.
• If the user provides a draft markdown prompt, run or recommend scripts/validate-prompt-example.py.
• If the adaptation involves manipulation, check safe-height and top-surface placement rules.
• If the adaptation involves navigation, check turn/move or waypoint conventions before writing code.
• If the request combines prompt adaptation and live execution, split the response across this sub-skill and ../airsim-simulator/.

Category routing

User intent	Best route inside this sub-skill
drone inspection, obstacle avoidance, Tello-like object search	references/category-map.md#aerial-robotics
visual object navigation, turn/move step traces	references/category-map.md#embodied-agents
pick/place/stack/push manipulation	references/category-map.md#manipulation
comparing robot, car, and drone controllers	references/category-map.md#multiple-robots
camera-based ball catching or SVG-style image reasoning	references/category-map.md#spatial-temporal-reasoning
generic robotics control, coordinate transforms, or controllers	references/category-map.md#basic-robotics

Prompt adaptation principles

• Preserve the list of allowed functions for the chosen robot.
• Ask a clarification question when object identity is ambiguous.
• Use only functions stated in the prompt context.
• Keep coordinate frames, units, and signs explicit.
• Prefer small, reviewable code snippets over large scripts unless the original example demonstrates an end-to-end script.
• Include an explanation when the repo's example style expects one.

Bundled helper

• scripts/validate-prompt-example.py checks a draft markdown prompt for core PromptCraft-Robotics structure signals.

Boundary with AirSim simulator

Some example categories mention AirSim drones, but example selection and adaptation still belongs here. Move to ../airsim-simulator/ only when the user asks about the runtime sample, its config files, wrapper functions, or API/runtime failures.