LightState Registry / Verified X Builder Use Cases / Finance & Deals / llm-api-model-routing-and-prompt-cache-finops
⚡ Pulse Score 80/100
LLM Token FinOps: Prompt Caching & Tiered Model Routing
Audit agent token usage logs to enforce prompt-prefix caching and route classification/extraction tasks to fast, low-cost models.
⚡ 1-Click Agent & Developer Install
Zero Auth · Ready for Grok Bot, Claude Code & Cursornpx lightstate inspect llm-api-model-routing-and-prompt-cache-finops
Copy-Paste System Prompt / Routine Blueprint:
Run the 'LLM Token FinOps: Prompt Caching & Tiered Model Routing' (llm-api-model-routing-and-prompt-cache-finops) implementation blueprint using Postgres MCP, Google Sheets MCP, GitHub MCP. Objective: Audit agent token usage logs to enforce prompt-prefix caching and route classification/extraction tasks to fast, low-cost models. Step 1: Perform a read-only audit of current state and recent logs. Step 2: Generate a deterministic execution plan with exact diffs, SQL/CLI commands, or drafted payloads. Step 3: Request human confirmation before applying any production writes or external sends.
Synthesized Engineering Blueprint & Setup Guide
### 1. Problem & Operational Bottleneck
Audit agent token usage logs to enforce prompt-prefix caching and route classification/extraction tasks to fast, low-cost models. Built and battle-tested in production workflows by **@ericosiu** (Eric Siu (@ericosiu)).
### 2. Target Architecture & Required Stack
- **Postgres MCP**
- **Google Sheets MCP**
- **GitHub MCP**
### 3. Step-by-Step Implementation Blueprint
1. Configure and authenticate the required MCP connectors (Postgres MCP, Google Sheets MCP, GitHub MCP) in your agent workspace.
2. Run the initial read-only inspection pass for 'LLM Token FinOps: Prompt Caching & Tiered Model Routing' to gather baseline telemetry, schemas, and context.
3. Execute the multi-step analysis and transformation pipeline with strict schema validation and zero fabricated identifiers.
4. Review the staged diff or approval card and verify completion via automated regression and status checks.
### 4. Copy-Paste Agent Execution Prompt
```markdown
Run the 'LLM Token FinOps: Prompt Caching & Tiered Model Routing' (llm-api-model-routing-and-prompt-cache-finops) implementation blueprint using Postgres MCP, Google Sheets MCP, GitHub MCP. Objective: Audit agent token usage logs to enforce prompt-prefix caching and route classification/extraction tasks to fast, low-cost models. Step 1: Perform a read-only audit of current state and recent logs. Step 2: Generate a deterministic execution plan with exact diffs, SQL/CLI commands, or drafted payloads. Step 3: Request human confirmation before applying any production writes or external sends.
```
### 5. Verification & Safety Guardrails
- **Human-in-the-Loop Gate:** All external communications, production database mutations, and billing actions stage an explicit review diff before execution.
- **Deterministic Telemetry:** Every run logs structured JSON output, latency metrics, and source citations so operators can audit every decision.
Tags: #postgres-mcp#google-sheets-mcp#github-mcp#blueprint#finance-deals
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