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chore: add more detail to contributing action guides - #172
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| - For an example, see [test_mint_nft.py](https://github.com/coinbase/agentkit/blob/master/cdp-agentkit-core/python/tests/actions/test_mint_nft.py) | ||
| 1. **Prompt**: A description that helps the AI understand when and how to use the action. It's important to describe the inputs and outputs of the action and include examples. Additionally, think about what inputs can be removed entirely and fetched or inferred by the LLM, so that users don't have to manually provide them. | ||
| 2. **Input Schema**: Define the input parameters using [Pydantic](https://docs.pydantic.dev/latest/) schemas. Pydantic is used to validate the inputs to the action and to generate a JSON schema that can be used by the LLM to understand the inputs. | ||
| 3. **Implementation Function**: The actual logic that executes the action. This function receives as input the wallet that the Agent has access to, and as you'll see in the walkthrough below, we can use this wallet to invoke an onchain contract! |
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@murrlincoln do you think this is an appropriate place to add the link out to CDP docs, as mentioned here?
| * The prompt disambuguates the type of NFT by specifying "ERC-721" | ||
| * The prompt specifies that the destination address should not be the contract address | ||
| * The prompt specifies that the LLM should ask the user for the destination address if it is unsure |
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can we add that in the case where there is a contract address taken as a parameter, the code either specifies the addresses or in some other way indexes for them? want to avoid the situation with morpho, where a user was required to find and input the address for the vault they wanted
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* chore: add more detail to contributing action guides * chore: add section on integration into ai frameworks
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* chore: add more detail to contributing action guides * chore: add section on integration into ai frameworks
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