IDKMesh

Non-package Python documentation reconciliation — 2026-10-13

Baseline: main@19043860b8358e9e78484876001b19063d697eec as observed through the connected GitHub API. Scope: direct Python sources in six non-package directories; this is a source-interface/entrypoint review, not a complete semantic, security or empirical-reproducibility audit.

Completed review

Compared the complete recursive Git tree against the source-level module purpose and exposed definitions of:

Created research module map and operational module map; each table links to real source files. The maps deliberately classify code by what the source describes and whether outputs are observation, synthetic evidence, metadata validation, or possibly external action. File inventory does not prove execution correctness. The associated test checks that each direct source file appears once in its owning map; it does not certify behavior.

Source-backed implementation boundaries

  1. experiments/local_verifier.py, patch v0.2-v0.4 adapters and experiments/local_validator.py inspect metadata, diff/provenance and files; they do not execute arbitrary candidate code. Explicit frozen-source behavioral probes are separate.
  2. experiments/two_attempt_orchestrator.py is a deterministic adapter/evidence control-plane kernel, not a live general swarm executor. run_evidence_report.py remains non-selecting. record_human_decision.py records a local human decision, not a GitHub merge.
  3. E016/E017 run fixed executable oracle/candidate studies and analyze actual oracle votes; other simulations remain synthetic. Upstream public SWE-bench matrices are observed data, but E045 is exploratory and E046/E048 have preregistration and temporal-holdout boundaries.
  4. interop/ maps semantic envelopes in process; it implements no generic A2A/MCP network server. Optional SDK tests can skip.
  5. tools/ and scripts/ have mixed risk: publication, GitHub, model and website tools can perform external I/O; a source link or dry-run helper never confers approval to execute them.

Validation

Next bounded passes

  1. Workflow-to-script invocation/permissions matrix with fail-closed checks, plus secret and action authority.
  2. Test-to-module traceability for untested entrypoints and a clean installation/real model environment replay.
  3. Review documented scientific claims and paper evidence against frozen results and registered revisions.
  4. Reconcile changing main and open PRs before future status changes; do not rewrite historical findings as current truth.

AI/tool provenance: ChatGPT with connected GitHub source access. No independent human review performed. Related stewardship tracker: #471.