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@promptbook/google

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Promptbook: Create persistent AI agents that turn your company's scattered knowledge into action

ptbk.io

webgptorg/promptbook

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/** * Resolves which projects one coding harness touched while answering a single message. * * The runtime log streams what the harness really did, so a project counts as touched when the * harness named it in a tool invocation — reading, searching, running, or editing files inside * `projects/<project-name>/`. Only tool payloads are inspected: tool results and assistant * narration are ignored so a project merely mentioned in the conversation is never reported. * * Every candidate is matched against the projects that really exist, which both filters prompt * placeholders such as `projects/<project-name>/` and keeps the reported names canonical. * * @param options - Raw runtime log content and the project directory names of the agent. * @returns Touched project names in the canonical spelling, ordered by first appearance. * @private internal utility of the agent-message runtime */ export declare function resolveAgentMessageTouchedProjectNames(options: { readonly logText: string | null | undefined; readonly knownProjectNames: ReadonlyArray<string>; }): ReadonlyArray<string>;