I built Replay because AI agent bills spike without a single warning or error in your logs when a prompt cache breaks. Whether your team runs Claude Code, Cursor, or Aider, the provider just silently re-bills your entire conversation history at cold-write prices instead of cached read prices.

Replay is a zero-telemetry, zero-dependency local Go CLI that forensically reads your on-disk log transcripts, replays them against reverse-engineered provider caching state-machines, and names the exact turn the cache broke, the cause, and the exact token leakage.

Repo: https://github.com/RedRobotKK/Replay

Core Subcommands (What it actually does):

- `replay` : Computes total avoidable re-billed cost across your local transcripts.

- `replay diff <transcript>` : Pinpoints the exact turn the cache sharded and why.

- `replay advise <dir>` : Outputs structural prompt optimization adjustments based on your history.

- `replay context <transcript>` : Ranks and isolates exactly what content is bloat-filling your context window.

- `replay route <dir> --to <model>` : Simulates what switching models would cost, factoring cold-start prefixes.

Why Go / Design Constraints:

1. Zero Dependency: Avoids messing with Python virtual environments or Docker runtimes for local diagnostics.

2. 100% Sandboxed: Absolutely no remote tracking, cloud accounts, or telemetry. Your prompt text never leaves your machine.

3. Mutant Testing Isolation: Keeps 76 real past defects frozen as re-runnable mutants to enforce code stability.

It's completely free and source-available (BUSL 1.1). To check your local developer logs or audit the setup script before running, use:

                curl -fsSL https://replay.doctor | less

Show HN: Replay – Audit silent prompt cache misses in AI agent transcripts