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### 1. The Workflow Bottleneck & Problem Statement Tweaking a system prompt to fix one edge case often silently breaks three other tool-calling workflows in production. ### 2. Synthesized Agent Architecture & Connected Stack **Automated System Prompt Regression & Tool-Call Accuracy Matrix** (`multi-model-prompt-eval-matrix`) is a verified production blueprint curated from **@alexalbert__**'s real-world implementation. - **Primary Capability:** Runs a 50-case golden evaluation suite whenever a production system prompt or MCP tool schema changes—scoring accuracy, refusal rates, and latency. - **Connected Tool Stack:** E2B Sandbox, SQLite MCP, GitHub MCP - **Execution Governance:** `Read-Only Discovery` → `Deterministic Policy Check` → `Ask-First Human Approval` - **Certified Builder Source:** [@alexalbert__](https://github.com/anthropics/courses) ### 3. Step-by-Step Implementation Blueprint 1. **Trigger & Data Ingestion:** Configure your agent routine to watch **E2B Sandbox** on a scheduled cadence or event webhook. Treat all external text as untrusted data inside XML fences. 2. **Cross-System Enrichment & Verification:** Query **SQLite MCP** to validate live capacity, account status, or code state before generating recommendations. 3. **Human-in-the-Loop Action Staging:** Post a structured summary card to **GitHub MCP** with 1-click approve/edit controls so your team retains full oversight. ### 4. Copy-Paste System Prompt & Routine Configuration ```text Implement the 'Automated System Prompt Regression & Tool-Call Accuracy Matrix' workflow curated with @alexalbert__. 1. OBJECTIVE: Runs a 50-case golden evaluation suite whenever a production system prompt or MCP tool schema changes—scoring accuracy, refusal rates, and latency. 2. CONNECTED TOOL STACK: E2B Sandbox, SQLite MCP, GitHub MCP 3. STEP-BY-STEP EXECUTION LOOP: - Step A (Ingest & Ground): Query live inputs from E2B Sandbox and cross-reference state in SQLite MCP. - Step B (Analyze & Validate): Apply strict filtering rules, verify schema/policy constraints, and flag any anomalies or missing fields. - Step C (Stage & Report): Prepare the structured output, draft replies/tickets in GitHub MCP, and request human confirmation before executing any external send or production write. ``` ### 5. Measured ROI & Production Impact - **Verified Outcome:** Provides quantitative pass/fail confidence before deploying any system prompt or tool schema update. - **Builder Portfolio:** [Explore all capabilities by @alexalbert__ →](/u/alexalbert__)

Tags: #multi-model-prompt-eval-matrix#use-case#engineering#alexalbert__#e2b-sandbox#sqlite-mcp

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