Frozen baseline: fb94d9dde0ccda83ae520ac6fb22b1d283562cf3, fetched from origin/main on 2026-10-11. Branch: experiment/codemode-bridge-20261011. This is a local experiment, not a change to the published CLI or MCP API.

The analyst question is whether composing REA's existing named tools in code improves investigation efficiency enough to justify an optional bridge. Existing users must keep their current names, input schemas, Evidence and session behavior. Provider analysis settings must stay identical between comparison profiles.

The bridge owns one upstream stdio MCP connection and discovers its complete live catalog. Only discovery and JavaScript execution are exposed downstream. Code calls tools.<original_name>(original_arguments) and receives the original MCP result envelope. REA still validates input, chooses providers, retains Evidence, and owns analysis resources. There is no second tool implementation or schema catalog to keep synchronized. A fresh QuickJS WASM context exposes only those tool calls, JSON helpers and explicit output; it has no host filesystem, network, process or module loader.

Start the bridge without changing an existing registration:

node bridge.mjs /absolute/path/to/node /absolute/path/to/rea/scripts/rea.mjs mcp

Register that command as a separate, temporary MCP server for a trial. Existing REA registrations keep their original tools. rea_search accepts a query or exact names; use schemas: false for the complete lightweight name/description list. Input schemas are returned by default. Request output_schemas: true when a result contract is needed; the original output schema is then returned unchanged. catalog_sha256 identifies the SDK catalog; it must not be substituted for REA's server_identity.catalog.digests fields. rea_execute accepts a JavaScript async function body. For example:

const session = json(await tools.binary_session({})).result;
return { open: session.open, identity: session.server_identity };

The returned projection is not a new Evidence record. calls preserves operation, argument/result digests, upstream errors and actual producer Evidence IDs when provided. The upstream ledger retains complete original Evidence for later views and exports. Non-Evidence session responses have no invented Evidence ID. Calls and executions sharing one active target are serialized; Promise.all currently provides composition rather than parallel provider execution.

npm test runs actual upstream and downstream stdio MCP against this checkout's compiled runtime. The standalone experiment's nine tests cover discovery parity, original results/errors, bulk promise settlement, host capability absence, CPU deadline recovery, retained Evidence after an error, unresolved promises and the two-tool downstream boundary. These tests do not establish real native/Android/ firmware provider behavior. A lifecycle regression revealed that the QuickJS job pump can allocate an additional context: the execution scope now owns every context at creation and releases them before the runtime. Increasing memory did not fix that regression.

Install experimental dependencies separately with npm ci in this directory. They do not change the production package or lockfile. Use the repository's pinned Node and npm versions. No binary, provider database or raw third-party source is committed. Corpus identities and upstream download locations are in corpus.json.

Measure three baselines: normal full-catalog MCP, discovery-only MCP, and Code Mode. Count discovery, input code, intermediate results, final output, errors and retries. Report actual wall time separately from model-facing turns and local token estimates. Existing summary/page/workflow tools are fair alternatives; do not manufacture a gain by forcing full output on the direct-tool baseline. Replay measurements establish mechanism costs, not model task accuracy or inference latency. Real-agent trials must additionally verify supported facts, source identity, omissions and preserved Evidence references.

agent-trial.py runs a real local Codex CLI with a disposable account/config and one MCP registration. It copies authentication only, removes the profile on every exit, and retains JSONL events, the answer and measured API usage outside the repo. It defaults to gpt-5.6-terra with high reasoning, as requested. Run one task under the resource wrapper:

python3 resource-run.py -- python3 agent-trial.py \
  --mode direct --prompt /absolute/path/question.txt \
  --output /absolute/path/new-trial-directory

Use --mode bridge for the experimental server; --mode client-code requests Codex's own Code Mode. Optional --providers selects a JSON object of explicit provider settings. No ambient environment snapshot is retained. A configured flag or a model's tool_mode does not prove the model actually composed tools or filtered an intermediate result. Inspect the transcript, and mark accuracy as unassessed until the requested facts and source support have been reviewed.

The supplied feedback is a research lead. Its Ghidra timing claim also changed auto-analysis options, so it does not isolate Code Mode's effect. Relevant primary sources: Cloudflare Code Mode, MCP patterns, Anthropic code execution, and QuickJS WASM.

Run expensive commands with python3 resource-run.py -- COMMAND ARGS... on Linux with a user systemd manager. It uses a transient scope with one CPU, a 4 GiB hard memory ceiling, a 3 GiB early-stop threshold, no swap, and a task ceiling. It refuses to start when less than 8 GiB is available and stops if host available memory drops below 4 GiB. These limits protect the host; a resource abort is a failed measurement, never a successful benchmark. Also cap Node and Java heaps.