FlightBox — AI skill for Claude Code
Record, replay, and diff every LLM call your AI agent makes.
How to install FlightBox
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open he-yufeng/FlightBox and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What FlightBox does
Record, replay, and diff every LLM call your AI agent makes.
Alternatives in AI
- Claude Replay — Convert AI coding agent sessions (Claude Code, Cursor, Codex, Gemini, OpenCode) into self-contained, embeddabl 644 ★
- Upstream Watch — Review pydantic-ai and pydantic-ai-harness releases published since the last watch entry, and record a verdict 361 ★
- Llmix — Production LLM call layer for AI agents and tools: keep OpenAI/Anthropic/AI SDK/LiteLLM, hot-swap models with 132 ★
README
[](https://pypi.org/project/flightbox/) [](https://pypi.org/project/flightbox/) [](LICENSE)
[**Quick Start**](#quick-start) · [**Record**](#record) · [**Replay**](#replay) · [**Diff**](#diff) · [中文](README_CN.md)

**Black-box flight recorder for AI agents** — record every LLM call your agent makes, replay sessions deterministically, and export a redacted evidence report when something breaks.
FlightBox is local-first. Recordings live in SQLite. No hosted dashboard is required.
Why
An agent failed and nobody can reproduce it. The final answer is in a log, but the interesting evidence is scattered across LLM requests, tool calls, model responses, timing, tokens, and local notes.
FlightBox gives you a deterministic debugging trail:
- record OpenAI / Anthropic / LiteLLM calls
- replay the same responses later
- diff two runs
- export JSONL or pytest replay tests
- generate a redacted Markdown / HTML report for PRs, CI notes, and teammates
Quick Start
pip install flightbox
Record
import flightbox
from openai import OpenAI
client = OpenAI()
with flightbox.record("debug-session") as rec:
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "What is 2+2?"}],
)
print(response.choices[0].message.content)
print(f"Recorded as run: {rec.run_id}")
Replay
import flightbox
with flightbox.replay("abc123def4"):
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "What i
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