openreflex 0.1.2

OpenReflex: muscle memory for AI coding agents

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What is OpenReflex

OpenReflex gives AI coding agents muscle memory. It plugs into Claude Code, Codex, Cursor, and OpenCode through lifecycle hooks and MCP, quietly records how each task actually went, and hands the next similar task what worked before: the approach, the files that mattered, and the fix for the error you hit last time.

You install it once and keep working normally. Everything stays on your machine in a local SQLite database. There is no account, no service, and no telemetry.

Why OpenReflex

• It remembers what worked. Before a substantial task, OpenReflex retrieves similar past tasks and injects a compact Execution Context: a suggested approach with alternatives, the files that were changed, and lessons such as which edit resolved a recurring error.
• It catches loops while they happen. Repeated failing commands, identical retries, stalled progress, and runaway context growth raise a single, specific alert with an alternative path, never a stream of nags.
• It learns after every task. OpenReflex infers the outcome from real verification (a test or build that passed or failed after the last edit), estimates Execution Regret against the alternatives, and extracts lessons.
• It is private by design. Only coarse, project-relative metadata is stored. File contents, commands, tool output, and transcripts never are, and capture is off until you approve a project.

        before a task                  during a task                 after a task
  ┌──────────────────────┐    ┌──────────────────────────┐    ┌───────────────────────┐
  │ retrieve experience  │    │ watch tool calls         │    │ infer outcome         │
  │ score candidate paths│ →  │ flag loops and stalls    │ →  │ estimate regret       │
  │ inject context       │    │ suggest an alternative   │    │ extract lessons       │
  └──────────────────────┘    └──────────────────────────┘    └───────────────────────┘
                 ▲                                                        │
                 └──────────────────── Experience Graph ◄─────────────────┘

Quick start

Requires Python 3.11 or newer.

pipx install openreflex            # or: uv tool install openreflex
cd your-project
openreflex install claude-code     # writes hooks + MCP config and enables this project

Then work as usual. After a few tasks:

openreflex context "fix the login redirect bug"   # preview the context a task would receive
openreflex status                                 # what has been captured and learned
openreflex doctor                                 # installation checks and recent hook errors

Use it with your agent

OpenReflex installs per project with openreflex install <agent>, or as a plugin.

With a plugin install, enable each project with openreflex approve. Claude Code is verified in live sessions; the Codex, Cursor, and OpenCode integrations follow each agent's documented hook protocol.

How it works

Hooks send lifecycle events (prompt, tool start, tool end, compaction, stop) to the OpenReflex engine, which stores them in an Experience Graph:

Task -caused-> Execution -used-> Context -used-> Experience
CandidatePath -recommended_for-> Task            Lesson -recommended_for-> Task
Execution -failed_with-> ToolCall -resolved_by-> ToolCall
Execution -caused-> Outcome -caused-> Experience -caused-> Lesson

• Before a task: similar experiences are retrieved, three strategies (inspect-first, test-first, incremental) are scored on success probability, time, tool calls, context cost, risk, uncertainty, and reversibility, and a context of at most 1,400 characters is injected. Nothing is injected without relevant experience.
• During a task: each alert fires at most once per task with a cooldown, and names a concrete alternative.
• After a task: outcome and chosen path come from the agent's record_outcome / choose_path MCP calls when available, and are otherwise inferred from tool activity. Execution Regret is withheld when the outcome is unknown.

Agents can also query OpenReflex directly through its MCP server: get_execution_context, choose_path, record_outcome, search_experience, explain_node, project_insights, and approve_project.

CLI

Privacy

• Stored per tool call: tool name, a coarse category (read, edit, search, test, ...), a fingerprint of the arguments, project-relative file paths, status, duration, output size, and a masked one-line error signature.
• Never stored: file contents, command text, tool output, transcripts, or paths outside the project.
• Prompts are kept as task descriptions (up to 1,000 characters) with secrets such as API keys and tokens redacted.
• Data lives in ~/.openreflex/projects/<hash>/experience.sqlite3. Set OPENREFLEX_HOME to move it, OPENREFLEX_DISABLE=1 to turn capture off everywhere, or run openreflex forget --yes to delete a project's data.

Community & Contributing

• Issues and ideas: GitHub Issues

• Support the project: Buy me a coffee

• Develop locally:

  git clone https://github.com/vishnu-77/openreflex && cd openreflex
  pip install -e ".[dev]"
  pytest && ruff check src tests scripts
  

License

OpenReflex is released under the MIT License.