> For the complete documentation index, see [llms.txt](https://docs.palliora.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.palliora.org/ai/build/for-agent-assisted-devs.md). # For agent-assisted developers More and more code against these docs is written by an AI coding agent on a person's behalf. This page says what an agent can rely on when building on Palliora AI specifically, and where it must not guess. This is the Palliora AI-specific companion to the core [For agent-assisted developers](https://github.com/palliora-org/palliora-docs-with-ai/tree/main/build/coding-agents/for-agent-assisted-devs.md) page. Read that one first; it covers the chain SDK generally. This page covers only what's specific to calling models. ## What to rely on * The code blocks in [Call a model](/ai/build/call-a-model.md), [Build a chat-completions-compatible service](/ai/build/chat-completions-service.md) and [Encrypted compute](https://github.com/palliora-org/palliora-docs-with-ai/tree/main/build/guides/encrypted-compute.md) are runnable as written against the live testnet, not illustrative pseudocode. * Known gaps are stated as gaps, not glossed over. The guardian result-key lookup problem in Encrypted Compute is a real, current limitation with a documented workaround, not something more reading will find a hidden fix for. ## Do not guess | Topic | The trap | The fact | | ------------------------------ | --------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Which model to use | Assuming any model name works | Guardians run a small, curated Ollama set: `gemma3:1b`, `deepseek-r1:1.5b`, `llama3.2:1b`, `qwen3:0.6b`. Any other model submits fine and fails at execution. | | Getting the answer | Expecting `inferenceCompute` to return it | It returns an agreement ID and block number. The answer lands later as a separate `compute.result` extrinsic you poll for. | | Poll window | Using the SDK's 20-block default | Real inference can take longer. Give it 300 blocks. | | Guardian result-encryption key | Reading `staking.guardians(address).pubKey` as the Ed25519 decryption key | That field is the guardian's sr25519 signing key. Feeding it to `gen_shared_key` throws. See [Encrypted compute](https://github.com/palliora-org/palliora-docs-with-ai/tree/main/build/guides/encrypted-compute.md#the-known-rough-edge-finding-nodepub) for the real workaround. | | Signing | Shipping `//Bob` (the dev-only account in every example) into anything real | It's shared and unsuited to production. Swap in a per-user signer before anything beyond a demo. | | Privacy | Assuming any of the plain guides hide the prompt | [Call a model](/ai/build/call-a-model.md) and the chat-completions example are both plaintext end to end. Only [Encrypted compute](https://github.com/palliora-org/palliora-docs-with-ai/tree/main/build/guides/encrypted-compute.md) hides the input. | ## Read these first 1. [`palliora-ai.skill.md`](/ai/build/palliora-ai.skill.md), a condensed version of this page plus the call pattern and common failures in one file. 2. [Call a model](/ai/build/call-a-model.md), the fastest path to a working call against the live testnet. 3. [Encrypted compute](https://github.com/palliora-org/palliora-docs-with-ai/tree/main/build/guides/encrypted-compute.md) before assuming a prompt is private just because it reached a Compute Contract. ## Safety rules for agents * Never run against mainnet with a real wallet without the person's go-ahead. * Don't hardcode the dev-only `//Bob` account into anything meant to run for real users. * Don't invent a `nodePub` value. If it isn't in the known-good map, say so instead of guessing one. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.palliora.org/ai/build/for-agent-assisted-devs.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.