OrcaReplay — Time travel for AI agents. Record, replay, fork, and debug any agent run with any model. Built by the OrcaRouter.ai team.
- ✓Open-source license (Apache-2.0)
- ✓Actively maintained (<30d)
- ✓Healthy fork ratio
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
git clone https://github.com/Continuum-AI-Corp/OrcaReplay && cp OrcaReplay/*.md ~/.claude/agents/Subagents overview
# OrcaReplay
<sub>**English** · [简体中文](docs/i18n/README.zh-CN.md) · [日本語](docs/i18n/README.ja.md) · [한국어](docs/i18n/README.ko.md) · [Deutsch](docs/i18n/README.de.md) · [Français](docs/i18n/README.fr.md) · [Español](docs/i18n/README.es.md) · [العربية](docs/i18n/README.ar.md)</sub>
### Your agent broke something at 2am. Replay it at 9am — exactly, offline, as many times as you like.
Record any coding agent. Reproduce the run byte-for-byte with the network off. Fork it from any step
onto a different model and see who gets it right.
<a href="https://www.orcarouter.ai">
<img src="docs/orcarouter.svg" alt="OrcaRouter" height="28" align="left" hspace="10">
</a>
**Built by the team behind [OrcaRouter](https://www.orcarouter.ai)** — one API key and one endpoint
for Claude, GPT, Gemini, Grok, DeepSeek, Qwen and the rest. It is what `orca setup` points at by
default, and what makes `orca compare` a single command instead of four provider accounts.
Find us: [OrcaRouter All model APIs](https://www.orcarouter.ai/models)
Github Repos: [OrcaCode Review](https://www.orcarouter.ai/code-review) · [OrcaRouter Lite](https://github.com/Continuum-AI-Corp/OrcaRouter-Lite)
Connect: [X](https://x.com/OrcaRouter) · [Discord](https://discord.com/invite/YEubt8enRA) · [Hugging Face](https://huggingface.co/orcarouter) · [Ollama](https://ollama.com/orcarouter)
<br clear="left">
[](LICENSE)
[](spec/orca-trace-v0.md)
[](#install)
[](#which-agents)
[](docs/good-first-issues.md)

<sup>Real output from one session — a Claude Code run recorded, replayed with the network off, then
forked at checkpoint 4 onto two models and graded by `npx tsc --noEmit`. Nothing here is mocked up.</sup>
## Try it in three commands
```console
orca record claude # your agent, unmodified, doing whatever it does
orca replay last # the same run again — no network, no tokens, no charge
orca replay last --from 4 --model claude-haiku-4-5 --ui
```
The third line is the one people stay for: same files, same conversation prefix, different model
from step 4 onward. The model is the only variable, which is what makes the answer mean anything.
```console
npm i -g orcareplay
```
## Read your agent's own system prompt
A proxy that sees the whole loop also sees the prompt the harness assembled before it sent
anything. One command captures it, scrubs the machine out of it, and files it by model:
```console
node capture/capture.mjs claude --model claude-opus-5
```
Interactive prompts and `-p` prompts are not the same prompt, and neither is the same across
models. See [`capture/README.md`](capture/README.md) for the measured differences, the pitfalls,
and the sanitising rules.
## Why this exists
Agent debugging today is archaeology. You scroll a terminal, you re-run and get a different
failure, you add print statements to someone else's harness. The tools that exist are
observability tools: they tell you a run cost $4.12 and used 61k tokens, which is not the question
you have. The question you have is *why did it delete my migration file.*
OrcaReplay answers that by giving you the run back.
| | Observability tools | OrcaReplay |
|---|---|---|
| Tells you what a run cost | ✅ | ✅ |
| Tells you which tool call deleted the file | sometimes | ✅ |
| Runs the agent again and gets the same answer | ❌ | ✅ offline, byte-for-byte |
| Lets you change the model and re-run from step 4 | ❌ | ✅ |
| Needs you to modify your agent | usually an SDK wrapper | ❌ two env vars |
| Works after you close the terminal | ❌ | ✅ it is a file |
| Sees past the model API — shell exit codes, file writes | ❌ | ✅ every turn |
| Records an agent with no API endpoint to redirect | ❌ | ✅ opt-in `--tls-intercept` |
The last two rows are the ones an SDK wrapper structurally cannot reach. Capture happens *below*
the agent — at the process and socket boundary — so it does not matter whether the agent is
yours, whether you can edit it, or whether it even holds an API key: a Codex CLI signed in with
a ChatGPT subscription talks to its own backend over TLS and has no base URL to point anywhere,
and orca can still record it. See
[when the harness will not be redirected](#when-the-harness-will-not-be-redirected).
## How it works
Model APIs are stateless, so on every turn an agent resends the entire conversation — including the
previous turn's tool results. **A proxy in front of the model therefore sees the whole loop**: each
request, each streamed response, every tool call the model emitted, and every tool result the
harness produced. That one property is what the tool is built on, and it is why **OrcaReplay does
not patch your agent** — it stands up a local proxy, sets two environment variables, and gets out of
the way.
Three more layers catch what the protocol cannot see: an exit code, a real duration, which stream a
byte came out of, a file written without telling anyone. A fifth exists for the agents that read no
base-URL variable at all — see [which agents](#which-agents).
```mermaid
%%{init: {'theme':'neutral'}}%%
flowchart LR
A["<b>your agent</b><br/><i>unmodified</i>"]
subgraph orca["orca · five capture layers"]
direction TB
P["<b>proxy</b><br/>base-URL env var"]
SH["<b>PATH shim</b><br/>exit code · timing · streams"]
MC["<b>JSON-RPC tee</b><br/>MCP config rewrite"]
FS["<b>shadow git index</b><br/>workspace per turn"]
FH["<b>fetch hook</b><br/>for a hardcoded origin"]
end
A --> P & SH & MC & FS & FH
P -->|"forwarded, auth intact"| U["<b>the model API</b><br/><i>or OrcaRouter · any gateway</i>"]
orca ==> T[("<b>one trace</b><br/>.orca/runs/run_a1b2c3")]
```
They all land in the same timeline, ordered by when they actually happened rather than when orca
got around to reading them.
### Exact, fork and compare are one thing
They are not three subsystems. They are the same proxy with a **cursor** — the position in the
recorded stream where it stops answering from disk and starts answering from the network.
```mermaid
%%{init: {'theme':'neutral'}}%%
flowchart LR
subgraph disk["from disk · byte-for-byte · network blocked"]
direction LR
T1["turn 1"] --> T2["turn 2"] --> T3["turn 3"] --> T4["turn 4"]
end
T4 ==> CUR{{"<b>cursor</b>"}}
CUR ==> T5
subgraph net["from the network · any model you name"]
direction LR
T5["turn 5"] --> T6["turn 6"] --> T7["…"]
end
```
| command | where the cursor sits | what you get |
|---|---|---|
| `orca replay last` | at the end | the whole run again, **network blocked** — no tokens, no charge, no variance |
| `orca replay last --from 4 --model X` | at checkpoint 4 | turns up to 4 identical, then a different model takes over |
| `orca compare last --from 4 --models a,b` | at checkpoint 4, several times | one table, one variable — the model |
A **checkpoint** is not recorded; it is *derived* — any point where the conversation prefix is
complete and the workspace was snapshotted. Every fork therefore starts from a state that provably
existed.
## What a bug hunt actually looks like
Your agent was supposed to fix a failing auth test. It exited 0 and the test still fails. Start with
what it actually did:
```console
$ orca show last
run_6473f858b59e generic-openai@0.1.0 14 events exit 0
SEQ KIND WHAT DETAIL
0 RUN run started generic-openai
1 SNAP tree 919d32ba037537b43814c83779963b2cc3023db7 0 changed
2 MODEL claude-opus-5 1 messages
3 MODEL claude-opus-5 stop: tool_use · 100 in · 20 out
4 TOOL edit_file {"path":"auth.ts",…}
5 SNAP tree c6af62b75c0c8b8938bd6087328b5148f3dcd534 1 changed
6 FILE auth.ts modified +1 −3
7 TOOL edit_file ok
8 MODEL claude-opus-5 3 messages
9 MODEL claude-opus-5 stop: end_turn · 101 in · 5 out
10 SNAP tree c6af62b75c0c8b8938bd6087328b5148f3dcd534 0 changed
11 SHELL ["sh","-c","node --check nonexistent-file.ts"] /tmp/hunt
12 SHELL shell result exit 1 · 43ms
13 RUN run ended exit 0
info usage input=201 output=25 cost=$0.004890
```
Three facts the model's own transcript could not have told you, and the run's exit code hid: the
file really changed (seq 6, `+1 −3`), the check the agent ran **failed** (seq 12, `exit 1`), and it
finished anyway. The run exited 0 because the *agent* exited 0.
That last fact is the one worth a command of its own. `orca show` gives you the order things
happened in; `orca graph` gives you what produced what:
```console
$ orca graph last
FROM TO KIND WHY
3 model.response 4 tool.call recorded tool_use block in the response
4 tool.call 6 fs.change inferred changed path appears in tool input, same or previous turn
4 tool.call 7 tool.result recorded tool result answers its call
7 tool.result 8 model.request recorded tool_result block in the request
11 shell.exec 12 shell.result recorded shell result answers its exec
1 inferred — derived from this trace, not recorded in it
```
Two kinds of edge, and the differeWhat people ask about OrcaReplay
What is Continuum-AI-Corp/OrcaReplay?
+
Continuum-AI-Corp/OrcaReplay is subagents for the Claude AI ecosystem. OrcaReplay — Time travel for AI agents. Record, replay, fork, and debug any agent run with any model. Built by the OrcaRouter.ai team. It has 171 GitHub stars and its last recorded update is dated 2026-09-08.
How do I install OrcaReplay?
+
You can install OrcaReplay by cloning the repository (https://github.com/Continuum-AI-Corp/OrcaReplay) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is Continuum-AI-Corp/OrcaReplay safe to use?
+
Our security agent has analyzed Continuum-AI-Corp/OrcaReplay and assigned a Trust Score of 100/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains Continuum-AI-Corp/OrcaReplay?
+
Continuum-AI-Corp/OrcaReplay is maintained by Continuum-AI-Corp. The last recorded GitHub activity is dated 2026-09-08, with 5 open issues.
Are there alternatives to OrcaReplay?
+
Yes. On ClaudeWave you can browse similar subagents at /categories/agents, sorted by popularity or recent activity.
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