Explore AI Agent Skills & Claude Prompts

action-and-motion-understanding

by Dingxingdi

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Use this skill when the user asks 'how many times did [action] happen?', 'what is the player doing?', 'where did the ball go?', 'is this a complex move?', 'what happens next?', or 'compare these two athletes'. It is triggered for tasks assessing high-frequency sports dynamics, counting rapid repetitive actions (like rally counts), identifying specific kinetic stroke techniques, predicting immediate athletic outcomes, and ranking technical difficulty based on observed action units.

open-domain-data-discovery-and-table-selection

by Dingxingdi

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Use this skill when the user wants questions that make the agent first figure out *which table matters* before doing the math. Trigger it for requests such as “make it search the right sheet first,” “make it find the relevant table from a pile of files,” “make the question depend on the correct spreadsheet,” or “make it choose the right data source before answering.” Also trigger it when the task should feel like open-domain analytics over many tables, not direct computation over a table that is already handed to the agent. Plain-language examples: “Ask something where the answer is hidden in one of many datasets,” “make it pick the right table by itself,” “make it search through messy tabular data first.”

open-domain-data-discovery-and-table-selection

by Dingxingdi

star 0

Use this skill when the user wants questions that make the agent first figure out *which table matters* before doing the math. Trigger it for requests such as “make it search the right sheet first,” “make it find the relevant table from a pile of files,” “make the question depend on the correct spreadsheet,” or “make it choose the right data source before answering.” Also trigger it when the task should feel like open-domain analytics over many tables, not direct computation over a table that is already handed to the agent. Plain-language examples: “Ask something where the answer is hidden in one of many datasets,” “make it pick the right table by itself,” “make it search through messy tabular data first.”

capacity-constrained-transport-coordination

by Dingxingdi

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Use this when the user wants planning data about moving several items with limited carrying ability, two hands, one hoist, or tight transport capacity. Trigger it for requests like 'make tasks where the robot can only carry a little at a time', 'give me move-things-between-rooms problems', 'create loading and unloading plans with bottlenecks', or 'make planning tasks where one carrier choice blocks another.'

capacity-constrained-transport-coordination

by Dingxingdi

star 0

Use this when the user wants planning data about moving several items with limited carrying ability, two hands, one hoist, or tight transport capacity. Trigger it for requests like 'make tasks where the robot can only carry a little at a time', 'give me move-things-between-rooms problems', 'create loading and unloading plans with bottlenecks', or 'make planning tasks where one carrier choice blocks another.'

hierarchical-semantic-navigation-planning

by Dingxingdi

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Use this when the user provides long-horizon navigation instructions in 3D environments that require following a sequence of landmarks, extracting map coordinates, or navigating based on functional zones and user-lifestyle demands. Trigger it for requests like 'follow the route from the bank to the park', 'I am a graphic designer, find a tidy spot for me to work', 'go to the study and organize my documents', or 'guide the drone over the damaged buildings in the satellite image'.

depth-and-dimensional-measurement

by Dingxingdi

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Trigger this skill when the user asks for questions about how far something is, how big it is, which point is closer, how tall a desk is, or whether an embodied agent can estimate physical size from what it sees. Plain-language triggers include: 'near or far,' 'how deep is that point,' 'how tall is the object,' 'measure the desk,' and 'questions about exact size instead of just naming things.'

causal-and-counterfactual-video-reasoning

by Dingxingdi

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Use this skill when the user asks questions like 'is this a crime?', 'is there an anomaly here?', 'is this person acting suspicious?', 'why did the fight break out?', 'is this area safe?', 'classify this dangerous event', or 'pinpoint the exact moment the robbery started'. Trigger it when the agent must distinguish between normal behavior and anomalous/illegal activities, deduce the hidden motives of actors in a conflict, or evaluate the causal progression of crimes and accidents in surveillance or open-world videos.

analytic-dataset-construction

by Dingxingdi

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Use this skill when the user wants the agent to *set up the right analysis table* before doing any statistics. Trigger it for requests such as “make it build the dataset first,” “make it pick variables, weights, and filters,” “calculate rolling aggregates/windows,” “find streaks of behavior,” or “make the real work be dataset setup.” Plain-language examples: “Ask something where the agent must prepare the analysis frame,” “make it decide who is in scope,” “analyze the data in batches of time,” or “make it choose the right columns and units before computing.”

empathetic-validation-and-active-listening

by Dingxingdi

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Use this skill when a user requires emotional support, feels distressed, or needs an expert to help them collaboratively make sense of a complex personal situation (like medical symptoms or life challenges) before jumping to solutions. It is triggered by requests involving emotional venting, counseling needs, or diagnostic confusion where the user might say 'I'm upset,' 'why do I feel this way,' 'can you make sense of these symptoms?', or 'help me figure out what's wrong.' Everyday examples include: 'I'm so stressed about my job loss,' 'help me understand my anxiety about public speaking,' and 'I've been feeling weird lately, why do my test results look like this?'

depth-and-dimensional-measurement

by Dingxingdi

star 0

Trigger this skill when the user asks for questions about how far something is, how big it is, which point is closer, how tall a desk is, or whether an embodied agent can estimate physical size from what it sees. Plain-language triggers include: 'near or far,' 'how deep is that point,' 'how tall is the object,' 'measure the desk,' and 'questions about exact size instead of just naming things.'

stateful-online-sequential-grounding-and-replanning

by Dingxingdi

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Trigger this skill when the agent is assigned a multi-step mission where later steps depend on information discovered in earlier steps, or when testing if the agent knows how far it has progressed through an instruction sequence. Plain-language triggers include: 'follow these steps one by one', 'go to the first place then the second', 'which step am I currently on?', 'how much of the task is done?', 'remember where the items were', and 'fix the plan if you can't find the next object'.