OpenReflex

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What is OpenReflex

OpenReflex gives AI coding agents ambient project muscle memory across coding, investigation, and reasoning work. Lifecycle hooks quietly record how work actually goes, compile repeated project behaviour into reusable Reflexes, and inject only the relevant project procedure into new tasks. The model does not need to remember to call OpenReflex, and MCP diagnostics are opt-in rather than loaded into normal agent context.

You install it once and keep working normally. Core memory stays on your machine in a local SQLite database. There is no OpenReflex account or hosted service. Optional Claude token accounting uses Claude Code's local OpenTelemetry export to a loopback-only OpenReflex receiver and stores counts only.

_{A recorded Claude Code session. OpenReflex injects compact relevant context before work; lifecycle hooks capture tools and verification and close the execution automatically. MCP is not required for the normal path. The step-by-step walkthrough is in docs/walkthrough.md.}

Why OpenReflex

• It learns how the project behaves. OpenReflex compiles successful work into project-scoped Reflexes such as authentication changes, Helm configuration, database migrations or CI work. Resolution combines semantic intent, task family and module/file locality, so a novel task can reuse a project procedure without repeating an earlier task.
• It catches loops while they happen. Repeated failing commands, identical retries, stalled progress, and runaway context growth raise one alert that says whether to continue, pivot to another approach, or stop and check in with you, never a stream of nags.
• It learns after every task. Build work closes against tests/lint/build evidence; investigations can close against cross-checked sources; reasoning-only work can complete without external tools. A simple Path check only names a better option when comparable past tasks actually support one.
• 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.

Quick start

Requires Python 3.11 or newer.

Claude Code — recommended: install the plugin, reload it, inspect the current state, then explicitly enable project memory.

/plugin marketplace add vishnu-77/openreflex
/plugin install openreflex@openreflex
/reload-plugins
/openreflex
/openreflex approve

Claude may display the canonical plugin namespace as /openreflex:openreflex; both refer to the same user-invoked OpenReflex control surface when the bare alias is available. The no-argument command is read-only and compact. approve explicitly enables local memory for the current project. The plugin prepares an exact-version runtime under ~/.openreflex/runtime/ and normal agent work remains ambient after approval.

The Claude plugin does not execute a global openreflex from PATH. An older pipx/uv/pip installation can coexist without taking over the plugin runtime.

CLI / other agents: use a persistent package install.

pipx install openreflex            # or: uv tool install openreflex
cd your-project
openreflex install codex           # or cursor / opencode / claude-code

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
openreflex update --check                         # check the latest stable release

Package updates preserve local memory and project configuration. Managed pipx and uv tool installs can use openreflex update, openreflex update --reinstall, or openreflex self reinstall. The Claude plugin manages its own pinned runtime automatically; these package-manager commands are only needed for standalone CLI installs.

Use it with your agent

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

With the Claude plugin, /openreflex shows a compact read-only state view. Use /openreflex approve to enable local memory for the current project, then work normally. Other explicit controls include status, reflexes, memory, doctor, why, trace, and revoke. OpenReflex control turns are not learned as project experiences and do not trigger normal task verification. The control skill is user-invoked only and does not enable MCP diagnostics or participate in normal model routing. Claude may show the canonical namespaced form /openreflex:openreflex. Per-agent guides: Claude Code, Codex, Cursor, OpenCode.

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 and OpenReflex first identifies the work mode. BUILD uses inspect-first, test-first, and incremental; INVESTIGATE uses source-first, cross-check, and broad-then-deep; THINK uses reason-first, compare-options, and evidence-first. Paths are ranked using past evidence, estimated cost, risk, uncertainty and reversibility. A compact context is injected only when relevant experience exists.
• During a task: when a detector finds a failure loop, repeated calls, stalled progress, context growth, or work past the budget, OpenReflex estimates the marginal value of more work. The current path's success estimate is updated with each call that makes no progress or fails, and compared with the cost of the work left and with the best untried alternative. The alert ends with a recommendation to continue, pivot to another strategy, or stop and ask the user. Each problem, pivot, or stop is raised once, with a cooldown between messages.
• After a task: lifecycle hooks close the execution automatically from work-mode-appropriate evidence; the model does not need to call OpenReflex. Explicit MCP outcome/path operations remain available only for manual or diagnostic workflows. The Path check says either better option: <path> when comparable completed tasks support it or better option: none proven. Recommendations are never presented as paths that were actually executed.

Every recommendation is stored as a decision snapshot with a Reflex Score (0-100): how strong the recommendation is, which is separate from the estimated chance that the task succeeds. openreflex why explains the latest decision and openreflex trace shows the timeline. In Claude Code, a short recap appears when a task starts, when OpenReflex recommends a pivot or stop or detects trouble, and when the task completes.

Set optional limits for every task with OPENREFLEX_BUDGET, for example calls=40,minutes=20,tokens=60000. Routing, scoring, budget and recap settings come from a versioned policy: the packaged defaults, overridden by ~/.openreflex/config.toml and then by .openreflex.toml in the project.

Normal work does not load OpenReflex MCP tools. If you explicitly want model-facing introspection for a project, enable it with openreflex diagnostics enable <agent>. Disable it again with openreflex diagnostics disable <agent>. The standalone MCP Registry package remains available for users who deliberately install OpenReflex as an MCP server.

The optional MCP diagnostics/admin tools

Tool	What it does
get_execution_context	Plan a task: similar past tasks, the suggested strategy with alternatives, a budget, likely files, lessons. Optional max_tool_calls, max_minutes, max_context_tokens.
check_progress	Whether more work on the current path is worth it: continue, pivot or stop.
choose_path	Declare the strategy being followed when it differs from the suggestion.
record_outcome	Record a confirmed outcome (tests/builds, cross-checked research, user confirmation, or failure) and learn from it.
explain_decision	Why the latest recommendation was made: Reflex Score, signals, confidence, next-best route.
get_execution_trace	The decision timeline of the most recent task.
get_reflex_score	The latest Reflex Score and its components as JSON.
search_experience	Past tasks in the project by description similarity, with their lessons.
explain_node	One Experience Graph node and its relations.
get_project_insights	What has been recorded, reused and learned in the project.
approve_project	Enable capture, only when the user explicitly asks.
forget_experience	Delete one past task's memory, only when the user explicitly asks.

CLI

Privacy

Data lives in ~/.openreflex/projects/<hash>/experience.sqlite3. Set OPENREFLEX_HOME to move it, OPENREFLEX_DISABLE=1 to turn capture off everywhere, openreflex forget --yes to delete a project's data, or ask your agent to forget_experience a single task.

Research

OpenReflex is also a research project in budget-aware execution: instead of treating success as a yes or no, it studies how agents choose execution paths, spend tool calls, model tokens and context, respond to uncertainty, and whether past work makes similar future work cheaper without reducing outcome quality. The loop is experience retrieval, evidence-aware path selection, budget-aware execution, work-mode-specific completion and plain-language path comparison. The Researcher view on the site explains the idea, lets you step through one reflex forming in the graph, and places it next to related work.

The reproducible evaluation protocol, pinned real-agent corpus, exact prompts, and claim boundaries are documented in docs/evaluation.md.

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
  

OpenReflex is listed in the MCP Registry as io.github.vishnu-77/openreflex and on Glama:

License

OpenReflex is released under the MIT License.