Agent Notes: background memory system that learns from emails, chats, and explicit
  saves

  - Background service (agent_notes.ts) runs periodically, collecting user-sent
  emails, copilot conversation history, and save-to-memory inbox entries
  - Agent (agent_notes_agent.ts) processes all sources with workspace tools, deciding
  what to update: user.md (timestamped facts), preferences.md (general rules),
  style/email.md (writing patterns), and topic-specific files as needed
  - save-to-memory builtin tool lets the copilot proactively note preferences during
  conversations
  - user.md and preferences.md injected into copilot system prompt on every turn;
  other files listed for on-demand access
  - Agent manages timestamp freshness on user.md: refreshes confirmed facts, removes
  stale transient ones
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@ -21,6 +21,7 @@ import { init as initEmailLabeling } from "@x/core/dist/knowledge/label_emails.j
import { init as initNoteTagging } from "@x/core/dist/knowledge/tag_notes.js";
import { init as initInlineTasks } from "@x/core/dist/knowledge/inline_tasks.js";
import { init as initAgentRunner } from "@x/core/dist/agent-schedule/runner.js";
import { init as initAgentNotes } from "@x/core/dist/knowledge/agent_notes.js";
import { initConfigs } from "@x/core/dist/config/initConfigs.js";
import started from "electron-squirrel-startup";
import { execSync } from "node:child_process";
@ -230,6 +231,9 @@ app.whenReady().then(async () => {
// start background agent runner (scheduled agents)
initAgentRunner();
// start agent notes learning service
initAgentNotes();
app.on("activate", () => {
if (BrowserWindow.getAllWindows().length === 0) {
createWindow();

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@ -30,6 +30,61 @@ import { getRaw as getNoteCreationRaw } from "../knowledge/note_creation.js";
import { getRaw as getLabelingAgentRaw } from "../knowledge/labeling_agent.js";
import { getRaw as getNoteTaggingAgentRaw } from "../knowledge/note_tagging_agent.js";
import { getRaw as getInlineTaskAgentRaw } from "../knowledge/inline_task_agent.js";
import { getRaw as getAgentNotesAgentRaw } from "../knowledge/agent_notes_agent.js";
const AGENT_NOTES_DIR = path.join(WorkDir, 'knowledge', 'Agent Notes');
function loadAgentNotesContext(): string | null {
const sections: string[] = [];
const userFile = path.join(AGENT_NOTES_DIR, 'user.md');
const prefsFile = path.join(AGENT_NOTES_DIR, 'preferences.md');
try {
if (fs.existsSync(userFile)) {
const content = fs.readFileSync(userFile, 'utf-8').trim();
if (content) {
sections.push(`## About the User\nThese are notes you took about the user in previous chats.\n\n${content}`);
}
}
} catch { /* ignore */ }
try {
if (fs.existsSync(prefsFile)) {
const content = fs.readFileSync(prefsFile, 'utf-8').trim();
if (content) {
sections.push(`## User Preferences\nThese are notes you took on their general preferences.\n\n${content}`);
}
}
} catch { /* ignore */ }
// List other Agent Notes files for on-demand access
const otherFiles: string[] = [];
const skipFiles = new Set(['user.md', 'preferences.md', 'inbox.md']);
try {
if (fs.existsSync(AGENT_NOTES_DIR)) {
function listMdFiles(dir: string, prefix: string) {
for (const entry of fs.readdirSync(dir)) {
const fullPath = path.join(dir, entry);
const stat = fs.statSync(fullPath);
if (stat.isDirectory()) {
listMdFiles(fullPath, `${prefix}${entry}/`);
} else if (entry.endsWith('.md') && !skipFiles.has(`${prefix}${entry}`)) {
otherFiles.push(`${prefix}${entry}`);
}
}
}
listMdFiles(AGENT_NOTES_DIR, '');
}
} catch { /* ignore */ }
if (otherFiles.length > 0) {
sections.push(`## More Specific Preferences\nFor more specific preferences, you can read these files using workspace-readFile. Only read them when relevant to the current task.\n\n${otherFiles.map(f => `- knowledge/Agent Notes/${f}`).join('\n')}`);
}
if (sections.length === 0) return null;
return `# Agent Memory\n\n${sections.join('\n\n')}`;
}
export interface IAgentRuntime {
trigger(runId: string): Promise<void>;
@ -418,6 +473,31 @@ export async function loadAgent(id: string): Promise<z.infer<typeof Agent>> {
return agent;
}
if (id === 'agent_notes_agent') {
const agentNotesAgentRaw = getAgentNotesAgentRaw();
let agent: z.infer<typeof Agent> = {
name: id,
instructions: agentNotesAgentRaw,
};
if (agentNotesAgentRaw.startsWith("---")) {
const end = agentNotesAgentRaw.indexOf("\n---", 3);
if (end !== -1) {
const fm = agentNotesAgentRaw.slice(3, end).trim();
const content = agentNotesAgentRaw.slice(end + 4).trim();
const yaml = parse(fm);
const parsed = Agent.omit({ name: true, instructions: true }).parse(yaml);
agent = {
...agent,
...parsed,
instructions: content,
};
}
}
return agent;
}
const repo = container.resolve<IAgentsRepo>('agentsRepo');
return await repo.fetch(id);
}
@ -773,7 +853,7 @@ export async function* streamAgent({
const provider = await isSignedIn()
? await getGatewayProvider()
: createProvider(modelConfig.provider);
const knowledgeGraphAgents = ["note_creation", "email-draft", "meeting-prep", "labeling_agent", "note_tagging_agent"];
const knowledgeGraphAgents = ["note_creation", "email-draft", "meeting-prep", "labeling_agent", "note_tagging_agent", "agent_notes_agent"];
const modelId = (knowledgeGraphAgents.includes(state.agentName!) && modelConfig.knowledgeGraphModel)
? modelConfig.knowledgeGraphModel
: modelConfig.model;
@ -951,6 +1031,13 @@ export async function* streamAgent({
timeZoneName: 'short'
});
let instructionsWithDateTime = `Current date and time: ${currentDateTime}\n\n${agent.instructions}`;
// Inject Agent Notes context for copilot
if (state.agentName === 'copilot' || state.agentName === 'rowboatx') {
const agentNotesContext = loadAgentNotesContext();
if (agentNotesContext) {
instructionsWithDateTime += `\n\n${agentNotesContext}`;
}
}
if (voiceInput) {
loopLogger.log('voice input enabled, injecting voice input prompt');
instructionsWithDateTime += `\n\n# Voice Input\nThe user's message was transcribed from speech. Be aware that:\n- There may be transcription errors. Silently correct obvious ones (e.g. homophones, misheard words). If an error is genuinely ambiguous, briefly mention your interpretation (e.g. "I'm assuming you meant X").\n- Spoken messages are often long-winded. The user may ramble, repeat themselves, or correct something they said earlier in the same message. Focus on their final intent, not every word verbatim.`;

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@ -37,6 +37,30 @@ Rowboat is an agentic assistant for everyday work - emails, meetings, projects,
**Slack:** When users ask about Slack messages, want to send messages to teammates, check channel conversations, or find someone on Slack, load the \`slack\` skill. You can send messages, view channel history, search conversations, and find users. Always show message drafts to the user before sending.
## Learning About the User (save-to-memory)
Use the \`save-to-memory\` tool to note things worth remembering about the user. This builds a persistent profile that helps you serve them better over time. Call it proactively — don't ask permission.
**When to save:**
- User states a preference: "I prefer bullet points"
- User corrects your style: "too formal, keep it casual"
- You learn about their relationships: "Monica is my co-founder"
- You notice workflow patterns: "no meetings before 11am"
- User gives explicit instructions: "never use em-dashes"
- User has preferences for specific tasks: "pitch decks should be minimal, max 12 slides"
**Capture context, not blanket rules:**
- BAD: "User prefers casual tone" this loses important context
- GOOD: "User prefers casual tone with internal team (Ramnique, Monica) but formal/polished with investors (Brad, Dalton)"
- BAD: "User likes short emails" too vague
- GOOD: "User sends very terse 1-2 line emails to co-founder Ramnique, but writes structured 2-3 paragraph emails to investors with proper greetings"
- Always note WHO or WHAT CONTEXT a preference applies to. Most preferences are situational, not universal.
**When NOT to save:**
- Ephemeral task details ("draft an email about X")
- Things already in the knowledge graph
- Information you can derive from reading their notes
## Memory That Compounds
Unlike other AI assistants that start cold every session, you have access to a live knowledge graph that updates itself from Gmail, calendar, and meeting notes (Google Meet, Granola, Fireflies). This isn't just summaries - it's structured extraction of decisions, commitments, open questions, and context, routed to long-lived notes for each person, project, and topic.
@ -187,6 +211,7 @@ ${runtimeContextPrompt}
- \`slack-checkConnection\`, \`slack-listAvailableTools\`, \`slack-executeAction\` - Slack integration (requires Slack to be connected via Composio). Use \`slack-listAvailableTools\` first to discover available tool slugs, then \`slack-executeAction\` to execute them.
- \`web-search\` and \`research-search\` - Web and research search tools (available when configured). **You MUST load the \`web-search\` skill before using either of these tools.** It tells you which tool to pick and how many searches to do.
- \`app-navigation\` - Control the app UI: open notes, switch views, filter/search the knowledge base, manage saved views. **Load the \`app-navigation\` skill before using this tool.**
- \`save-to-memory\` - Save observations about the user to the agent memory system. Use this proactively during conversations.
**Prefer these tools whenever possible** they work instantly with zero friction. For file operations inside \`~/.rowboat/\`, always use these instead of \`executeCommand\`.

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@ -1260,4 +1260,25 @@ export const BuiltinTools: z.infer<typeof BuiltinToolsSchema> = {
}
},
},
'save-to-memory': {
description: "Save a note about the user to the agent memory inbox. Use this when you observe something worth remembering — their preferences, communication patterns, relationship context, scheduling habits, or explicit instructions about how they want things done.",
inputSchema: z.object({
note: z.string().describe("The observation or preference to remember. Be specific and concise."),
}),
execute: async ({ note }: { note: string }) => {
const inboxPath = path.join(WorkDir, 'knowledge', 'Agent Notes', 'inbox.md');
const dir = path.dirname(inboxPath);
await fs.mkdir(dir, { recursive: true });
const timestamp = new Date().toISOString();
const entry = `\n- [${timestamp}] ${note}\n`;
await fs.appendFile(inboxPath, entry, 'utf-8');
return {
success: true,
message: `Saved to memory: ${note}`,
};
},
},
};

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@ -0,0 +1,333 @@
import fs from 'fs';
import path from 'path';
import { WorkDir } from '../config/config.js';
import { createRun, createMessage } from '../runs/runs.js';
import { bus } from '../runs/bus.js';
import { serviceLogger } from '../services/service_logger.js';
import { loadUserConfig } from '../pre_built/config.js';
import {
loadAgentNotesState,
saveAgentNotesState,
markEmailProcessed,
markRunProcessed,
type AgentNotesState,
} from './agent_notes_state.js';
const SYNC_INTERVAL_MS = 10 * 1000; // 10 seconds (for testing)
const EMAIL_BATCH_SIZE = 5;
const RUNS_BATCH_SIZE = 5;
const GMAIL_SYNC_DIR = path.join(WorkDir, 'gmail_sync');
const RUNS_DIR = path.join(WorkDir, 'runs');
const AGENT_NOTES_DIR = path.join(WorkDir, 'knowledge', 'Agent Notes');
const INBOX_FILE = path.join(AGENT_NOTES_DIR, 'inbox.md');
const AGENT_ID = 'agent_notes_agent';
// --- File helpers ---
function ensureAgentNotesDir(): void {
if (!fs.existsSync(AGENT_NOTES_DIR)) {
fs.mkdirSync(AGENT_NOTES_DIR, { recursive: true });
}
}
// --- Email scanning ---
function findUserSentEmails(
state: AgentNotesState,
userEmail: string,
limit: number,
): string[] {
if (!fs.existsSync(GMAIL_SYNC_DIR)) {
return [];
}
const results: { path: string; mtime: number }[] = [];
const userEmailLower = userEmail.toLowerCase();
function traverse(dir: string) {
const entries = fs.readdirSync(dir);
for (const entry of entries) {
const fullPath = path.join(dir, entry);
const stat = fs.statSync(fullPath);
if (stat.isDirectory()) {
if (entry !== 'attachments') {
traverse(fullPath);
}
} else if (stat.isFile() && entry.endsWith('.md')) {
if (state.processedEmails[fullPath]) {
continue;
}
try {
const content = fs.readFileSync(fullPath, 'utf-8');
const fromLines = content.match(/^### From:.*$/gm);
if (fromLines?.some(line => line.toLowerCase().includes(userEmailLower))) {
results.push({ path: fullPath, mtime: stat.mtimeMs });
}
} catch {
continue;
}
}
}
}
traverse(GMAIL_SYNC_DIR);
results.sort((a, b) => b.mtime - a.mtime);
return results.slice(0, limit).map(r => r.path);
}
function extractUserPartsFromEmail(content: string, userEmail: string): string | null {
const userEmailLower = userEmail.toLowerCase();
const sections = content.split(/^---$/m);
const userSections: string[] = [];
for (const section of sections) {
const fromMatch = section.match(/^### From:.*$/m);
if (fromMatch && fromMatch[0].toLowerCase().includes(userEmailLower)) {
userSections.push(section.trim());
}
}
return userSections.length > 0 ? userSections.join('\n\n---\n\n') : null;
}
// --- Inbox reading ---
function readInbox(): string[] {
if (!fs.existsSync(INBOX_FILE)) {
return [];
}
const content = fs.readFileSync(INBOX_FILE, 'utf-8').trim();
if (!content) {
return [];
}
return content.split('\n').filter(l => l.trim());
}
function clearInbox(): void {
if (fs.existsSync(INBOX_FILE)) {
fs.writeFileSync(INBOX_FILE, '');
}
}
// --- Copilot run scanning ---
function findNewCopilotRuns(state: AgentNotesState): string[] {
if (!fs.existsSync(RUNS_DIR)) {
return [];
}
const results: string[] = [];
const files = fs.readdirSync(RUNS_DIR).filter(f => f.endsWith('.jsonl'));
for (const file of files) {
if (state.processedRuns[file]) {
continue;
}
try {
const fullPath = path.join(RUNS_DIR, file);
const fd = fs.openSync(fullPath, 'r');
const buf = Buffer.alloc(512);
const bytesRead = fs.readSync(fd, buf, 0, 512, 0);
fs.closeSync(fd);
const firstLine = buf.subarray(0, bytesRead).toString('utf-8').split('\n')[0];
const event = JSON.parse(firstLine);
if (event.agentName === 'copilot') {
results.push(file);
}
} catch {
continue;
}
}
results.sort();
return results;
}
function extractConversationMessages(runFilePath: string): { role: string; text: string }[] {
const messages: { role: string; text: string }[] = [];
try {
const content = fs.readFileSync(runFilePath, 'utf-8');
const lines = content.split('\n').filter(l => l.trim());
for (const line of lines) {
try {
const event = JSON.parse(line);
if (event.type !== 'message') continue;
const msg = event.message;
if (!msg || (msg.role !== 'user' && msg.role !== 'assistant')) continue;
let text = '';
if (typeof msg.content === 'string') {
text = msg.content.trim();
} else if (Array.isArray(msg.content)) {
text = msg.content
.filter((p: { type: string }) => p.type === 'text')
.map((p: { text: string }) => p.text)
.join('\n')
.trim();
}
if (text) {
messages.push({ role: msg.role, text });
}
} catch {
continue;
}
}
} catch {
// ignore
}
return messages;
}
// --- Wait for agent run completion ---
async function waitForRunCompletion(runId: string): Promise<void> {
return new Promise(async (resolve) => {
const unsubscribe = await bus.subscribe('*', async (event) => {
if (event.type === 'run-processing-end' && event.runId === runId) {
unsubscribe();
resolve();
}
});
});
}
// --- Main processing ---
async function processAgentNotes(): Promise<void> {
const userConfig = loadUserConfig();
if (!userConfig) {
console.log('[AgentNotes] No user config found, skipping');
return;
}
ensureAgentNotesDir();
const state = loadAgentNotesState();
// Collect all source material
const messageParts: string[] = [];
// 1. Emails
const emailPaths = findUserSentEmails(state, userConfig.email, EMAIL_BATCH_SIZE);
if (emailPaths.length > 0) {
messageParts.push(`## Emails sent by ${userConfig.name}\n`);
for (const p of emailPaths) {
const content = fs.readFileSync(p, 'utf-8');
const userParts = extractUserPartsFromEmail(content, userConfig.email);
if (userParts) {
messageParts.push(`---\n${userParts}\n---\n`);
}
}
}
// 2. Inbox entries
const inboxEntries = readInbox();
if (inboxEntries.length > 0) {
messageParts.push(`## Notes from the assistant (save-to-memory inbox)\n`);
messageParts.push(inboxEntries.join('\n'));
}
// 3. Copilot conversations
const newRuns = findNewCopilotRuns(state);
const runsToProcess = newRuns.slice(-RUNS_BATCH_SIZE);
if (runsToProcess.length > 0) {
let conversationText = '';
for (const runFile of runsToProcess) {
const messages = extractConversationMessages(path.join(RUNS_DIR, runFile));
if (messages.length === 0) continue;
conversationText += `\n--- Conversation ---\n`;
for (const msg of messages) {
conversationText += `${msg.role}: ${msg.text}\n\n`;
}
}
if (conversationText.trim()) {
messageParts.push(`## Recent copilot conversations\n${conversationText}`);
}
}
// Nothing to process
if (messageParts.length === 0) {
return;
}
const serviceRun = await serviceLogger.startRun({
service: 'agent_notes',
message: 'Processing agent notes',
trigger: 'timer',
});
try {
const timestamp = new Date().toISOString();
const message = `Current timestamp: ${timestamp}\n\nProcess the following source material and update the Agent Notes folder accordingly.\n\n${messageParts.join('\n\n')}`;
const agentRun = await createRun({ agentId: AGENT_ID });
await createMessage(agentRun.id, message);
await waitForRunCompletion(agentRun.id);
// Mark everything as processed
for (const p of emailPaths) {
markEmailProcessed(p, state);
}
for (const r of newRuns) {
markRunProcessed(r, state);
}
if (inboxEntries.length > 0) {
clearInbox();
}
state.lastRunTime = new Date().toISOString();
saveAgentNotesState(state);
await serviceLogger.log({
type: 'run_complete',
service: serviceRun.service,
runId: serviceRun.runId,
level: 'info',
message: 'Agent notes processing complete',
durationMs: Date.now() - serviceRun.startedAt,
outcome: 'ok',
summary: {
emails: emailPaths.length,
inboxEntries: inboxEntries.length,
copilotRuns: runsToProcess.length,
},
});
} catch (error) {
console.error('[AgentNotes] Error processing:', error);
await serviceLogger.log({
type: 'error',
service: serviceRun.service,
runId: serviceRun.runId,
level: 'error',
message: 'Error processing agent notes',
error: error instanceof Error ? error.message : String(error),
});
}
}
// --- Entry point ---
export async function init() {
console.log('[AgentNotes] Starting Agent Notes Service...');
console.log(`[AgentNotes] Will process every ${SYNC_INTERVAL_MS / 1000} seconds`);
// Initial run
await processAgentNotes();
// Periodic polling
while (true) {
await new Promise(resolve => setTimeout(resolve, SYNC_INTERVAL_MS));
try {
await processAgentNotes();
} catch (error) {
console.error('[AgentNotes] Error in main loop:', error);
}
}
}

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@ -0,0 +1,90 @@
export function getRaw(): string {
return `---
tools:
workspace-writeFile:
type: builtin
name: workspace-writeFile
workspace-readFile:
type: builtin
name: workspace-readFile
workspace-edit:
type: builtin
name: workspace-edit
workspace-readdir:
type: builtin
name: workspace-readdir
workspace-mkdir:
type: builtin
name: workspace-mkdir
---
# Agent Notes
You are the Agent Notes agent. You maintain a set of notes about the user in the \`knowledge/Agent Notes/\` folder. Your job is to process new source material and update the notes accordingly.
## Folder Structure
The Agent Notes folder contains markdown files that capture what you've learned about the user:
- **user.md** Facts about who the user IS: their identity, role, company, team, projects, relationships, life context. NOT how they write or what they prefer. Each fact is a timestamped bullet point.
- **preferences.md** General preferences and explicit rules (e.g., "don't use em-dashes", "no meetings before 11am"). These are injected into the assistant's system prompt on every chat.
- **style/email.md** Email writing style patterns, bucketed by recipient context, with examples from actual emails.
- Other files as needed If you notice preferences specific to a topic (e.g., presentations, meeting prep), create a dedicated file for them (e.g., \`presentations.md\`, \`meeting-prep.md\`).
## How to Process Source Material
You will receive a message containing some combination of:
1. **Emails sent by the user** Analyze their writing style and update \`style/email.md\`. Do NOT put style observations in \`user.md\`.
2. **Inbox entries** Notes the assistant saved during conversations via save-to-memory. Route each to the appropriate file. General preferences go to \`preferences.md\`. Topic-specific preferences get their own file.
3. **Copilot conversations** User and assistant messages from recent chats. Extract lasting facts about the user and append timestamped entries to \`user.md\`.
## What Goes Where Be Strict
### user.md ONLY identity and context facts
Good examples:
- Co-founded Rowboat Labs with Ramnique
- Team of 4 people
- Previously worked at Twitter
- Planning to fundraise after Product Hunt launch
- Based in Bangalore, travels to SF periodically
Bad examples (do NOT put these in user.md):
- "Uses concise, friendly scheduling replies" this is style, goes in style/email.md
- "Frequently replies with short confirmations" this is style, goes in style/email.md
- "Uses the abbreviation PFA" this is style, goes in style/email.md
- "Requested a children's story about a scientist grandmother" this is an ephemeral task, skip entirely
- "Prefers 30-minute meeting slots" this is a preference, goes in preferences.md
### style/email.md Writing patterns from emails
Organize by recipient context. Include concrete examples quoted from actual emails.
- Close team (very terse, no greeting/sign-off)
- External/investors (casual but structured)
- Formal/cold (concise, complete sentences)
### preferences.md Explicit rules and preferences
Things the user has stated they want or don't want.
### Other files Topic-specific persistent preferences ONLY
Create a new file ONLY for recurring preference themes where the user has expressed multiple lasting preferences about a specific skill or task type. Examples: \`presentations.md\` (if the user has stated preferences about slide design, deck structure, etc.), \`meeting-prep.md\` (if they have preferences about how meetings are prepared).
Do NOT create files for:
- One-off facts or transient situations (e.g., "looking for housing in SF" that's a user.md fact, not a preference file)
- Topics with only a single observation
- Things that are better captured in user.md or preferences.md
## Rules
- Always read a file before updating it so you know what's already there.
- For \`user.md\`: Format is \`- [ISO_TIMESTAMP] The fact\`. The timestamp indicates when the fact was last confirmed.
- **Add** new facts with the current timestamp.
- **Refresh** existing facts: if you would add a fact that's already there, update its timestamp to the current one so it stays fresh.
- **Remove** facts that are likely outdated. Use your judgment: time-bound facts (e.g., "planning to launch next week", "has a meeting with X on Friday") go stale quickly. Stable facts (e.g., "co-founded Rowboat with Ramnique", "previously worked at Twitter") persist. If a fact's timestamp is old and it describes something transient, remove it.
- For \`preferences.md\` and other preference files: you may reorganize and deduplicate, but preserve all existing preferences that are still relevant.
- **Deduplicate strictly.** Before adding anything, check if the same fact is already captured even if worded differently. Do NOT add a near-duplicate.
- **Skip ephemeral tasks.** If the user asked the assistant to do a one-off thing (draft an email, write a story, search for something), that is NOT a fact about the user. Skip it entirely.
- Be concise bullet points, not paragraphs.
- Capture context, not blanket rules. BAD: "User prefers casual tone". GOOD: "User prefers casual tone with internal team but formal with investors."
- **If there's nothing new to add to a file, do NOT touch it.** Do not create placeholder content, do not write "no preferences recorded", do not add explanatory notes about what the file is for. Leave it empty or leave it as-is.
- **Do NOT create files unless you have actual content for them.** An empty or boilerplate file is worse than no file.
- Create the \`style/\` directory if it doesn't exist yet and you have style content to write.
`;
}

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@ -0,0 +1,62 @@
import fs from 'fs';
import path from 'path';
import { WorkDir } from '../config/config.js';
const STATE_FILE = path.join(WorkDir, 'agent_notes_state.json');
export interface AgentNotesState {
processedEmails: Record<string, { processedAt: string }>;
processedRuns: Record<string, { processedAt: string }>;
lastRunTime: string;
}
export function loadAgentNotesState(): AgentNotesState {
if (fs.existsSync(STATE_FILE)) {
try {
const parsed = JSON.parse(fs.readFileSync(STATE_FILE, 'utf-8'));
// Handle migration from older state without processedRuns
if (!parsed.processedRuns) {
parsed.processedRuns = {};
}
return parsed;
} catch (error) {
console.error('Error loading agent notes state:', error);
}
}
return {
processedEmails: {},
processedRuns: {},
lastRunTime: new Date(0).toISOString(),
};
}
export function saveAgentNotesState(state: AgentNotesState): void {
try {
fs.writeFileSync(STATE_FILE, JSON.stringify(state, null, 2));
} catch (error) {
console.error('Error saving agent notes state:', error);
throw error;
}
}
export function markEmailProcessed(filePath: string, state: AgentNotesState): void {
state.processedEmails[filePath] = {
processedAt: new Date().toISOString(),
};
}
export function markRunProcessed(runFile: string, state: AgentNotesState): void {
state.processedRuns[runFile] = {
processedAt: new Date().toISOString(),
};
}
export function resetAgentNotesState(): void {
const emptyState: AgentNotesState = {
processedEmails: {},
processedRuns: {},
lastRunTime: new Date().toISOString(),
};
saveAgentNotesState(emptyState);
}

View file

@ -9,6 +9,7 @@ export const ServiceName = z.enum([
'voice_memo',
'email_labeling',
'note_tagging',
'agent_notes',
]);
const ServiceEventBase = z.object({