Daily Trigger

The trigger is a daily scheduled run. I'll now fetch the Reddit feeds from both subreddits and introspect the Notion database simultaneously.

Now let me fetch comments from the most relevant posts to get more details on real use-cases:

Now let me fetch comments from a few more relevant posts:

Now let me check the existing Notion database items to avoid duplicates, and also fetch comments from a couple more relevant posts:

I have enough data from the Reddit feeds and comments. Now I'll identify the unique, well-defined use-cases from today's posts that are not already in the Notion database, and create entries for them. Based on my analysis, I've identified these new use-cases:

1. Ad Spend Monitoring Agent with Inventory-Aware Pause Logic - from the post about ads running on out-of-stock products
2. Agent Cost Observability and Real-Time Budget Enforcement System - from the multi-agent cost tracking discussion
3. AI Agent Safety Guardrail Layer with Pre-Launch Audit and Action Classification - from the guardrails discussion
4. Extract-Then-Write Documentation Agent with Scratch Inventory and Gap Detection - from the documentation-generating skill post
5. AI Agent for Medical Free-Text to Clinical Code Mapping with Abstention and Drift Detection - from the health systems data/API failures post
6. Adaptive Agent Memory with Expiry-Based Stale Context Pruning - from the agent memory post

All 6 new use-cases have been successfully created in the Notion database. Here's a summary of what was accomplished in this daily run:

Reddit Sources Monitored:

• r/AI_Agents (hot feed, 25 posts scanned)
• r/aiagents (rate limited, unavailable)

Comments Fetched:

• Post on AI agent guardrails before public launch
• Post on multi-agent cost tracking ($1.8k incident)
• Post on documentation-generating skill with extract-then-write rule
• Post on data/API causing downstream agent failures in health systems

6 New Use-Cases Added to Notion:

1. Inventory-Aware Ad Spend Monitoring Agent — Automatically pauses/resumes ad campaigns based on product stock levels, preventing silent budget waste on sold-out products.

2. Real-Time Multi-Agent Cost Observability System — Per-session budget caps, compounding context detection, and per-call model identity logging to prevent runaway costs in multi-agent systems.

3. Pre-Launch AI Agent Safety Layer — Action classification into reversibility tiers, propose-execute separation, per-run tool call caps, and append-only audit logs outside the agent loop.

4. Extract-Then-Write Documentation Agent — Enforces scratch inventory extraction before writing, diffs against required fields, batches gap questions, and flags assumptions inline.

5. Clinical Free-Text to Medical Code Mapping Agent — Abstention option for unmappable inputs, versioned candidate sets, decision logging, and vocabulary drift detection via abstention rate monitoring.

6. Agent Memory System with Tiered Expiry — Three-bucket memory (rules, successes, failures with expiry), replace-not-stack correction policy, and explicit delete path to prevent stale context accumulation.